Biotechnology Progress最新文献

The quality control of RNA has become increasingly crucial with the rise of mRNA-based vaccines and therapeutics. However, conventional methods such as LC–MS often require specialized equipment and expertise, limiting their applicability to high throughput experiments. Here, we optimize a previously characterized RNA integrity biosensor, that provides a simple colorimetric output, using Design of Experiments (DoE). Through iterative rounds of a Definitive Screening Design (DSD) and experimental validation, we systematically explored different assay conditions to enhance the biosensor's performance. Optimization led to a 4.1-fold increase in dynamic range and reduced RNA concentration requirements by one-third, significantly improving usability. Notable modifications included reducing the concentrations of reporter protein and poly-dT oligonucleotide and increasing DTT concentration, suggesting a reducing environment for optimal functionality. Importantly, the optimized biosensor retained its ability to discriminate between capped and uncapped RNA even at lower RNA concentrations. Overall, our improved biosensor offers enhanced performance and reduced sample requirements, paving the way for rapid, cost-effective RNA quality control in diverse settings, including resource-limited environments.

The organ transplantation field requires new approaches for replacing and regenerating tissues due to the lack of adequate transplant methods. Three-dimensional (3D) extrusion-based bioprinting is a rapid prototyping approach that can engineer 3D scaffolds for tissue regeneration applications. In this process, 3D printed cell-based constructs, consisting of biomaterials, growth factors, and cells, are formed by the extrusion of bioinks from nozzles. However, extrusion applies shear stresses to cells, often leading to cellular damage or membrane rupture. To address this limitation, herein, we developed and optimized a 3D bioprinting approach by evaluating the effect of key extrusion-based 3D bioprinting parameters—bioink viscosity, nozzle size, shape, and printing speed—on cell viability. Our results revealed that cells printed in higher-viscosity bioinks, with smaller, cylindrical nozzles, exhibited lower viability due to their exposure to high shear stresses. Translational flow speed had a cell-dependent impact, as different cell types have different sensitivities to the magnitude and duration of shear stress inside the nozzle. Overall, evaluating these parameters could facilitate the development of 3D high-resolution bioprinted constructs for tissue regeneration applications, offering a more efficient alternative to traditional fabrication methods, which are often labor intensive, expensive, and repetitive.

Mammalian cell lines used for clinical studies and post-approval production of recombinant DNA-derived biotherapeutics are expected to be derived from a single cell, and regulatory submissions are expected to provide robust evidence of monoclonality. Imaged single-cell deposition followed by whole-well imaging using specialized instruments has, in many cell line development labs, replaced the “gold standard” of two rounds of limiting dilution due to its increased speed and the assurance of clonality provided by orthogonal images. However, there is still a lack of information on how the procedures used to define these clonal cell lines perform. Here we use a mixture of two distinguishable Chinese hamster ovary (CHO) cells to document that a greater than 99% probability of clonality can be obtained from our single-cell cloning method that uses our preparation procedures, the VIPS® single-cell deposition instrument, the Cell Metric® whole-well imager, and a comprehensive visual review. Together with the assurance of cell/well images, the determination of the probability of clonality of our VIPS+Cell Metric method provides a strong package of evidence of single-cell derivation of a recombinant CHO cell line.

Bacillus subtilis is a favored chassis for high productivity of several high value-added product in synthetic biology. Efficient production of recombinant proteins is critical but challenging using this chassis because these expression systems in use, such as constitutive and inducible expression systems, demand for coordination of cell growth with production and addition of chemical inducers. These systems compete for intracellular resources with the host, eventually resulting in dysfunction of cell survival. To overcome the problem, in this study, LuxRI quorum sensing (QS) system from Aliivibrio fischeri was functionally reconstituted in B. subtilis for achieving coordinated protein overproduction with cell growth in a cell-density-dependent manner. Furthermore, the output-controlling promoter, P_luxI, was engineered through two rounds of evolution, by which we identified four mutants, P22, P47, P56, and P58 that exhibited elevated activity compared to the original P_luxI. By incorporating a strong terminator (TB5) downstream of the target gene further enhanced expression level. The expression level of this system surpasses commonly used promoter-based systems in B. subtilis like P43 and P_ylbP. The LuxRI QS system proves to be a potent platform for recombinant protein overproduction in B. subtilis.

Arboviruses significantly burden public health in Brazil, constituting a constant challenge for health authorities. The diagnosis and, consequently, clinical management and the reporting of arbovirus infections in regions where multiple arboviruses coexist are complex processes. Herein, we report the development of a new electrochemical biosensor based on Concanavalin A (ConA) to identify carbohydrate patterns in the viral structure of Dengue 3 (DENV-3), Zika (ZIKV) and Chikungunya (CHIKV) viruses. The biorecognition of arboviruses was carried out through functionalization with 4-aminophenylacetic acid (CMA) on poly (ethylene terephthalate) (PET) substrate coated with a gold layer combining microcontact printing (μCP). Bovine serum albumin (BSA) was used after ConA immobilization to block binding to nonspecific sites. Subsequently, the interaction between ConA and arbovirus was characterized by standard atomic force microscopy (AFM), fluorescence microscopy, cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS). Fluorescent imaging was conducted to confirm the occurrence of the DENV-3, ZIKV, and CHIKV detection processes. The obtained results demonstrated the success of the biosensor (CMA-ConA-BSA) manufactured on a PET substrate using μCP for detecting medically significant arboviruses. RCT values showed an increase in impedimetric response total of the system after exposition to DENV-3 (RCT = 68.82 kΩ) and a lower recognition to CHIKV (RCT = 44.44 kΩ). The present biosensor platform reveals the applicability of the ConA lectin in the viral biorecognition process based on flexible biosensors for differential detection of DENV-3, ZIKV, and CHIKV. ConA-based electrochemical biosensor provide high selectivity, real-time detection, and low volumes of analytes.

Oil degumming process involves the removal of gums, which is required to improve the physicochemical and storage properties of the vegetable oils. Degumming of oils can be carried out by using chemicals, membranes (polymeric, inorganic, and ceramic), or enzymes, for example, phospholipases. Phospholipases are enzymes of tremendous significance in the degumming process as they convert gums to fatty acids and lipophilic substances. They provide a cost-effective and safe alternative to other degumming processes without affecting the oil yield. Lysophospholipases (LPLs) are highly valuable tools for degumming vegetable oils. LPLs can hydrolyze fatty acyl ester bonds of phosphatidylcholine at the sn-1 and sn-2 positions of glycerol moiety. In addition, they have the ability to catalyze hydrolysis lysophospholipids' ester bond either at sn-1 or sn-2 position. In this review, biotechnological production and biochemical characteristics of LPLs from three domains of life are highlighted. In comparison to bacterial and eukaryotic LPLs, archaeal LPLs were found to be active at high temperatures. Broad substrate specificity and thermostability of archaeal LPLs make them ideal candidates for the industrial degumming of oils. However, improvement of activity and substrate specificity of archaeal LPLs is required for enhancing their industrial utility. In the current review, various protein-engineering approaches (directed evolution, rational design, site-saturation mutagenesis, and fusion technology) as well as in silico tools have been discussed to increase the commercial significance of LPLs.

Recombinant adeno-associated virus (rAAV) is one of the most widely used viral vectors for gene therapy. It is used in very high doses for the treatment of many diseases, making large-scale production for clinical applications challenging. We have established a synthetic biology-based platform to construct stable production cell lines, which can be induced to produce rAAV2. In this study, we extended our cell line construction pipelines for rAAV2 to rAAV8, a serotype whose tropism makes it attractive for gene delivery in multiple tissues. The Genome Module, encoding the rAAV2 genome, and Replication Modules, containing Rep68, DBP and E4orf6 coding sequences, originally used for rAAV2 were retained, but the Packaging Module was modified to replace the AAV2 intron-less cap gene (VP123) with that of AAV8. These three genetic modules were integrated into HEK293 genome to generate four rAAV8 producer cell lines VH1-4, which all produced rAAV8 upon induction. Their productivity was similar to the initial rAAV2 producer cell lines GX2/6 constructed using the same pipeline, but was much lower than conventional triple plasmid transfection. We identified Cap protein production and capsid formation as a potential limiting factor, just as we observed in GX2/6. By integrating more copies of AAV8 VP123 into VH3 clone, the encapsidated rAAV8 titer increased 20-fold to a level comparable to triple transfection. By tuning induction conditions to modulate capsid production, the full particle content could be elevated. This study demonstrated that our rAAV producer cell line development platform is robust and applicable to different AAV serotypes.

Surfactants like polysorbate (Tween®) are commonly used as excipients in the production of monoclonal antibodies and other recombinant proteins. The retention behavior of these excipients in the final ultrafiltration step can be difficult to predict due to the presence of both monomers and micelles. This study examined the retention of polysorbate during ultrafiltration through cellulose and polyethersulfone membranes with nominal molecular weight cutoffs of 10, 30, and 100 kDa. Novel flux stepping experiments were performed to examine the effects of concentration polarization on surfactant transmission. Polysorbate 20 transmission through the 30 kDa membrane was a strong function of the surfactant concentration, decreasing from nearly 100% for a 2.5 mg/L solution to <10% for a 50 mg/L solution due to high retention of the micelles. Polysorbate transmission was lower for the polyethersulfone membrane due to polysorbate adsorption. A simple mathematical model was developed to describe the polysorbate transmission accounting for the effects of concentration polarization as well as the presence of surfactant monomers and micelles. Model calculations were in good agreement with the experimental data, providing a framework for the analysis and design of ultrafiltration/diafiltration processes for biopharmaceutical formulations containing surfactants.

As the industry continues to explore the benefits of continuous and intensified manufacturing, it is important to assure that the cell line development (CLD) workflows in practice today are well suited to generate clones that meet the unique challenges associated with these processes. Most cell lines used in intensified processes are currently developed using traditional fed-batch CLD workflows followed by adaptation of these cell lines to perfusion processes. This method maybe suboptimal as fed-batch CLD workflows select clones which produce high volumetric titers irrespective of cell growth rate and specific productivity (qP). Although sufficient for fed-batch processes, performance of cells derived from this traditional CLD workflow may not be maintained in perfusion processes, where an intricate balance of performance parameters is needed. Until now, a thorough investigation into the effect of the CLD workflow on top clone performance in perfusion processes has not been conducted. Here, we show how the CLD workflow impacts cell performance in both fed-batch and perfusion processes, emphasizing the advantages of adopting a perfusion-specific CLD workflow which includes the use of medium specially designed for expansion and production in a perfusion setting, scale-down models which more accurately simulate perfusion process, and the adoption of perfusion-specific cell line selection criteria. Together, this results in the development of more efficient cell lines, fit for continuous and intensified processing.

Machine learning (ML) techniques have emerged as an important tool improving the capabilities of online process monitoring and control in cell culture process for biopharmaceutical manufacturing. A variety of advanced ML algorithms have been evaluated in this study for cell growth monitoring using spectroscopic tools, including Raman and capacitance spectroscopies. While viable cell density can be monitored real-time in the cell culture process, online monitoring of cell viability has not been well established. A thorough comparison between the advanced ML techniques and traditional linear regression method (e.g., Partial Least Square regression) reveals a significant improvement in accuracy with the leading ML algorithms (e.g., 31.7% with Random Forest regressor), addressing the unmet need of continuous monitoring viability in a real time fashion. Both Raman and capacitance spectroscopies have demonstrated success in viability monitoring, with Raman exhibiting superior accuracy compared to capacitance. In addition, the developed methods have shown better accuracy in a relatively higher viability range (>90%), suggesting a great potential for early fault detection during cell culture manufacturing. Further study using ML techniques for VCD monitoring also showed an increased accuracy (27.3% with Raman spectroscopy) compared to traditional linear modeling. The successful integration of ML techniques not only amplifies the potential of process monitoring but also makes possible the development of advanced process control strategies for optimized operations and maximized efficiency.