Biotechnology Progress最新文献

Erlenmeyer shake flasks are widely used during the first steps of bioprocess development. Despite their broad application in academia and industry, shake flasks usually lack standardized and user-friendly online monitoring techniques. In this work, the pH and Respiratory Activity MOnitoring System (pH-RAMOS) for the non-invasive online measurement of the oxygen transfer rate (OTR), carbon dioxide transfer rate (CTR), and pH in up to eight parallel shake flasks under sterile conditions is presented. The OTR and CTR are quasi-continuously measured in the headspace of the shake flasks using dedicated oxygen and carbon dioxide sensors, enabling precise respiratory quotient (RQ) evaluation. Self-adhesive pH sensor spots are used for the high-frequent real-time pH monitoring of the culture. These prototype pH sensor spots stand out due to their simple sterilizability and subsequent one-point calibration in the cultivation medium. The long-term stability of the pH sensor spots was assessed in a 28-day long abiotic experiment. The novel pH-RAMOS was validated with different eukaryotic and prokaryotic microorganisms, such as Ogataea polymorpha, Ustilago trichophora, and Vibrio natriegens. The combination of online OTR, CTR, RQ, and pH signals allowed for identifying various metabolic phenomena, such as oxygen limitations, substrate limitations, diauxies, and the production or consumption of specific compounds, based on their degree of reduction or change of pH. The high-frequent and sensitive pH-monitoring was particularly advantageous for registering subtle and transient metabolic phenomena.

Uric acid (UA) is an antioxidant that has been reported to be a neuroprotective compound for injuries and diseases, and specifically, diseases of the central nervous system. However, uric acid is highly insoluble in aqueous solutions, and high levels in the serum lead to gout, which limits its use in humans. Here, we develop a novel drug delivery platform that will release uric acid in a sustained manner for application to neural tissue. We demonstrate that one-step incorporation of UA into an electrospun gelatin/hyaluronic acid nanofiber mat results in controlled release of UA in culture medium. Taking a unique approach, we made solutions of 12% gelatin and 1% hyaluronic acid in a formic acid solvent and added UA for production of nanofiber mats. We then dehydrothermally crosslinked the mats and tested for release of UA into physiological cell culture medium. To test whether the mats have any detrimental effects on healthy nervous system tissue, we cultured spinal cord explants on the mats extended and assessed extensions from the explants. We observed that comparable numbers and lengths of dendrites are extended from the spinal cord tissue, regardless of the amount UA content in the mats. Our results suggest that electrospun gelatin/hyaluronic acid nanofibers can be used as a platform for sustained uric acid delivery to neural tissue without detrimental effects.

Microbial decontamination is a critical concern in various sectors, from healthcare to food processing. Traditional decontamination methods, while effective to a degree, present limitations in terms of environmental impact, efficiency, and potential harm to the target material. This review investigates the emerging realm of non-thermal plasma (NTP) as a promising alternative for microbial decontamination, emphasizing its mechanisms, reactor designs and applications. The mechanism decomposed into physical, chemical and biological effects of plasma, are elaborated upon to provide a foundational understanding of the intrinsic principles of plasma decontamination. Except for the generation type of NTP, reactors and other parameters by which NTP achieves microbial decontamination, emphasizing the design considerations and parameters that influence its efficacy. Moreover, the latest applications of NTP in decontaminating air, water, and surfaces, supported by the latest research findings in each domain are explored. Additionally, the perspectives on the future research tendencies of NTP decontamination and disinfection are highlighted with potential avenues for exploration and innovation. Through this comprehensive review, the aim is to underscore the potential of NTP, particularly DBD plasma, as a versatile, efficient, and environmentally friendly method for microbial decontamination.

This study aimed to propose a methodology for developing a mechanistic model for viral clearance of the minute virus of mice (MVM) on flow-through anion exchange (AEX) chromatography. Protein surface analysis was applied to investigate the possibility of molecular interaction between the recombinant biotherapeutic and MVM. The protein product-free Tris buffers were spiked with MVM, and the MVM elution profile from AEX chromatography was quantitatively analyzed using quantitative polymerase chain reaction (qPCR) for pooled fractions. GoSilico™ Chromatography Modeling Software was applied to develop the mechanistic models for MVM species. For evaluating the visual fit of the developed model, the R² of intact MVM virions and uncoated capsids between the simulated and measured amount in each fraction are 0.880 and 0.948, respectively. Response surface plots of logarithmic reduction values (LRV) against pH and conductivity in loaded sample were generated to show the range for suitable loaded sample conditions for achieving a good LRV. To evaluate the applicability of the developed MVM elution model to a recombinant biotherapeutic, two demonstrations of AEX chromatography purification were performed with a loaded sample of a model monoclonal antibody. The peaks of the MVM species in the elution step of both runs were accurately simulated by the developed model. In addition, to assess the possibility of molecular interaction between the virus and the target protein significantly affecting the MVM elution behavior, the antibody's surface was evaluated in terms of hydrophobicity/hydrophilicity using surface analysis.

The challenging task of designing biopharmaceutical downstream processes is initially to select the type of unit operations, followed by optimizing their operating conditions. For complex flowsheet optimizations, the strategy becomes crucial in terms of duration and outcome. In this study, we compared three optimization strategies, namely, simultaneous, top-to-bottom, and superstructure decomposition. Moreover, all strategies were evaluated by either using chromatographic Mechanistic Models (MMs) or Artificial Neural Networks (ANNs). An overall evaluation of 39 flowsheets was performed, including a buffer-exchange step between the chromatography operations. All strategies identified orthogonal structures to be optimal, and the weighted overall performance values were generally consistent between the MMs and ANNs. In terms of time-efficiency, the decomposition method with MMs stands out when utilizing multiple cores on a multiprocessing system for simulations. This study analyses the influence of different optimization strategies on flowsheet optimization and advices on suitable strategies and modeling techniques for specific scenarios.

Bispecific antibodies (bsAbs) can simultaneously bind two different antigens or epitopes. Their dual-targeting capability enables novel mechanisms of action, gaining therapeutic advantages over conventional monospecific mAbs. In recent years, the number of bsAbs grows rapidly and bsAbs under development are available in diverse formats. In particular, Fc-containing IgG-like bsAbs, which represent the major group, can be constructed in asymmetric or symmetric format. For asymmetric ones, whose assembly requires multiple distinct chains, although numerous strategies have been developed to promote desired chain pairing, product-related variants such as free chains, half molecules and mispaired species are usually present at various levels. For symmetric ones, increased level of aggregates and truncating variants is often associated with their production. In general, bsAbs pose greater challenges to the downstream team than regular mAbs. In the past few years, our team successfully developed the downstream process for over 70 bsAbs in greater than 30 different formats and accumulated substantial experience. This review introduces general strategies that we have used while purifying these challenging molecules.

Tryptamines play diverse roles as neurotransmitters and psychoactive compounds found in various organisms. Psilocybin, a notable tryptamine, has garnered attention for its therapeutic potential in treating mental health disorders like depression and anxiety. Despite its promising applications, current extraction methods for psilocybin are labor-intensive and economically limiting. We suggest biocatalysis as a sustainable alternative, leveraging enzymes to synthesize psilocybin and other tryptamines efficiently. By elucidating psilocybin biosynthesis pathways, researchers aim to advance synthetic methodologies and industrial applications. This review underscores the transformative potential of biocatalysis in enhancing our understanding of tryptamine biosynthesis and facilitating the production of high-purity psilocybin and other tryptamines for therapeutic and research use.

Optimizing a biopharmaceutical chromatographic purification process is currently the greatest challenge during process development. A lack of process understanding calls for extensive experimental efforts in pursuit of an optimal process. In silico techniques, such as mechanistic or data driven modeling, enhance the understanding, allowing more cost-effective and time efficient process optimization. This work presents a modeling strategy integrating quantitative structure property relationship (QSPR) models and chromatographic mechanistic models (MM) to optimize a cation exchange (CEX) capture step, limiting experiments. In QSPR, structural characteristics obtained from the protein structure are used to describe physicochemical behavior. This QSPR information can be applied in MM to predict the chromatogram and optimize the entire process. To validate this approach, retention profiles of six proteins were determined experimentally from mixtures, at different pH (3.5, 4.3, 5.0, and 7.0). Four proteins at different pH's were used to train QSPR models predicting the retention volumes and characteristic charge, subsequently the equilibrium constant was determined. For an unseen protein knowing only the protein structure, the retention peak difference between the modeled and experimental peaks was 0.2% relative to the gradient length (60 column volume). Next, the CEX capture step was optimized, demonstrating a consistent result in both the experimental and QSPR-based methods. The impact of model parameter confidence on the final optimization revealed two viable process conditions, one of which is similar to the optimization achieved using experimentally obtained parameters. The multiscale modeling approach reduces the required experimental effort by identification of initial process conditions, which can be optimized.

Technology scale-up and transfer are a fundamental and critical part of process development in biomanufacturing. Important bioreactor hydrodynamic characteristics such as working volume, overhead gas flow rate, volumetric power input (P/V), impeller type, agitation regimen, sparging aeration strategy, sparger type, and k_La must be selected based on key performance indicators (KPI) to ensure a smooth and seamless process scale-up and transfer. Finding suitable operational setpoints and developing an efficient feeding regimen to ensure process efficacy and consistency are instrumental. In this investigation, process development of a cumate inducible Chinese hamster ovary (CHO) stable pool expressing trimeric SARS-CoV-2 spike protein in 1.8 L benchtop stirred-tank bioreactors is detailed. Various dissolved oxygen levels and aeration air caps were studied to determine their impact on cell growth and metabolism, culture longevity, and endpoint product titers. Once hydrodynamic conditions were tuned to an optimal zone, various feeding strategies were explored to increase culture performance. Dynamic feedings such as feeding based on current culture volume, viable cell density (VCD), oxygen uptake rate (OUR), and bio-capacitance signals were tested and compared to standard bolus addition. Increases in integral of viable cell concentration (IVCC) (1.25-fold) and protein yield (2.52-fold), as well as greater culture longevity (extension of 5 days) were observed in dynamic feeding strategies when compared to periodic bolus feeding. Our study emphasizes the benefits of designing feeding strategies around metabolically relevant signals such as OUR and bio-capacitance signals.

Healthcare-associated infections (HAIs) pose significant challenges to global health due to pathogen complexity and antimicrobial resistance. Biosensors utilizing antimicrobial peptides offer innovative solutions. Hylarana picturata Multiple Active Peptide 1 (Hp-MAP1), derived from Temporin-PTA, exhibits antibacterial properties sourced from the skin secretions of the Malaysian fire-bellied frog. An innovative sensing layer was developed for the electrochemical biorecognition of diverse pathogens: Pseudomonas aeruginosa, Klebsiella pneumoniae, Escherichia coli, and Staphylococcus aureus. Electrochemical impedance spectroscopy differentiated microorganisms based on distinct electrochemical responses. The sensor layer, composed of functionalized multi-walled carbon nanotubes (MWCNTs) associated with Hp-MAP1, exhibited varying levels of charge transfer resistance (R_CT) for different microorganisms. Gram-negative species, especially P. aeruginosa, displayed higher R_CT values, indicating better impedimetric responses. Excellent LODs were observed for P. aeruginosa (0.60), K. pneumoniae (0.42), E. coli (0.67), and S. aureus (0.59), highlighting the efficacy of the MWCNTs/Hp-MAP1 biosensor in microbial identification. The MWCNTs/Hp-MAP1 biosensor platform presents a promising and effective microbial identification strategy with potential healthcare applications to mitigate HAIs and enhance patient care.