Large-scale fermentation processes involve complex dynamic interactions between mixing, reaction, mass transfer, and the suspended biomass. Empirical correlations or case-specific computational simulations are usually used to predict and estimate the performance of large-scale bioreactors based on data acquired at bench scale. In this two-part-study, one-dimensional axial diffusion equations were studied as a general and predictive model of large-scale bioreactors. This second part focused on typical fed-batch operations where substrate gradients are known to occur, and characterized the profiles of substrate, pH, oxygen, carbon dioxide, and temperature. The physically grounded steady-state axial diffusion equations with first- and zeroth-order kinetics yielded analytical solutions to the relevant variables. The results were compared with large-scale Escherichia coli and Saccharomyces cerevisiae experiments and simulations from the literature, and good agreement was found in substrate profiles. The analytical profiles obtained for dissolved oxygen, temperature, pH, and CO 2 were also consistent with the available data. Distribution functions for the substrate were defined, and efficiency factors for biomass growth and oxygen uptake rate were derived. In conclusion, this study demonstrated that axial diffusion equations can be used to model the effects of mixing and reaction on the relevant variables of typical large-scale fed-batch fermentations.

Enabling real-time monitoring and control of the biomanufacturing processes through product quality insights continues to be an area of focus in the biopharmaceutical industry. The goal is to manufacture products with the desired quality attributes. To realize this rigorous attribute-focused Quality by Design (QbD) approach, it’s critical to support the development of processes that consistently deliver high-quality products and facilitate product commercialization. Time delays associated with off-line analytical testing can limit the speed of process development. Thus, developing and deploying analytical technology is necessary to accelerate process development. In this study, we have developed the Micro Sequential Injection (µSI) process analyzer and the Automatic Assay Preparation Platform (A2P2) system. These innovations address the unmet need for an automatic, online, real-time sample acquisition and preparation platform system for in-process monitoring, control, and release of biopharmaceuticals. These systems can also be deployed in laboratory areas as an off-line analytical system and on the manufacturing floor to enable rapid testing and release of products manufactured in a GMP environment.

Enzymes that catalyze post-translational modifications of peptides and proteins (PTM-enzymes) – proteases, protein ligases, oxidoreductases, kinases, and other transferases - are foundational to our understanding of health and disease and empower applications in chemical biology, synthetic biology, and biomedicine. To fully harness the potential of PTM-enzymes, there is a critical need to decipher their enzymatic and biological mechanisms, develop molecules that can probe and reprogram them, and endow them with improved and novel functions. These objectives are contingent upon implementation of high-throughput functional screens and selections that interrogate large sequence libraries to isolate desired PTM-enzyme properties. This review discusses the principles of S. cerevisiae organelle sequestration to study and engineer PTM-enzymes. These include methods that modify yeast surface display and employ enzyme-mediated transcription activation to evolve the activity and substrate specificity of proteases and protein ligases. We also present a detailed discussion of yeast endoplasmic reticulum (ER) sequestration for the first time. Where appropriate, we highlight the major features and limitations of different systems, specifically how they can measure and control enzyme catalytic efficiencies. Taken together, yeast-based high-throughput sequestration approaches significantly lower the barrier to understanding how PTM-enzymes function and how to reprogram them.

Genome-scale metabolic models provide a valuable resource to study metabolism and cell physiology. These models are employed with approaches from the constraint-based modelling framework to predict metabolic and physiological phenotypes. The prediction performance of genome-scale metabolic models can be improved by including protein constraints. The resulting protein-constrained models consider data on turnover numbers (kcat) and facilitate the integration of protein abundances. In this systematic review, we present and discuss the current state-of-the-art regarding the estimation of kinetic parameters used in protein-constrained models. We also highlight how data-driven and constraint-based approaches can aid the estimation of turnover numbers and their usage in improving predictions of cellular phenotypes. Lastly, we identify standing challenges in protein-constraint metabolic models and provide a perspective regarding future approaches to improve the predictive performance.

Biomaterials are important tools for the reconstruction of organs and tissues, and silica is widely used in these reconstruction technologies. Hence, a lexical and content analysis was carried out on articles on application of silica in biomaterials, based on a search in the Capes’ Journals Portal using the keywords “silica, biomedical, application, scaffold”, between the years 2009 and 2019. The 110 selected articles were analyzed using the IRaMuTeQ software, Word Cloud and Descending Hierarchical Classification (DHC). The words: “silica, cell, nanosilica, bone, material, scaffold and application” appear prominently in the Word Cloud and DHC indicating four classes: (1) physical characterization, (2) biomedicine applications, (3) engineering applications and (4) compatibility characterization. Thus, the analysis of DHC and Word Cloud showed that the main ways of using silica are: mesoporous silica nanoparticles, amorphous silica, silica-based materials, nanofibers and silica hybrids, and the main biomaterials developed are scaffolds, grafts, aerogels, hydrogels, membranes and drug delivery systems.

Targeted gene knockdown has become one of the most powerful tools in molecular biology and holds substantial promise in therapeutic applications. While existing technologies such as siRNAs, CRISPRi, and ASOs effectively and specifically reduce gene expression, few can be used to first discover the genes that influence a particular phenotype and then directly transition to being used as oligonucleotide therapeutics. Thus, a tool that could help bridge the gap between target discovery and the development of therapeutic leads would benefit the scientific community. Here, we present hnRNPA1 recruiting oligonucleotides, or AROs, as single-stranded RNA (ssRNA) molecules that knockdown transcript levels of target genes. AROs target specific pre-mRNA transcripts via sequence homology and leverage the ubiquitous and abundant endogenous RNA-binding protein hnRNPA1 to degrade target transcripts. Using RT-qPCR, we show that AROs effectively knock down target genes when delivered via a plasmid and expressed using a Pol II promoter or when delivered directly as single-strand RNAs. Additionally, as proof of principle, we use a ssRNA ARO to knockdown KRT14 in squamous cell carcinoma and show reduced invasive potential. We believe AROs fill an important niche in the scientific toolbox by taking advantage of endogenous RNA binding machinery for RNA knockdowns.

Abstract Generally, investigations on nanomedicine involve conventional imaging techniques for obtaining static images on nanoparticle internalization at a single time point where various phases can be overlooked. In contrast, 3D live-cell imaging can be used for obtaining cellular retention of drugs at various phases, and cells can be followed for days. This article demonstrates the application of time-lapse microscopy in the investigation of Poly-L-lysine coated ZnO nanoparticle dynamics. In this work, a laser scanning confocal microscope has been employed to quantify the dynamics of internalization particles and reactive oxygen species generation (ROS) using volumetric imaging. Firstly, we show that simultaneous spatial mapping of nanoparticle uptake in MCF-7 cells and ROS in a single cell can be used to identify the interdependence between the accumulation of particles and ROS generation. Secondly, monitoring of ROS formation and cytotoxicity using the same imaging platform offers an advantage over monitoring these parameters using various instruments. Finally, the ability of the fluorescent particles in inducing a significant reduction in cell viability suggests its potential to be used as a therapeutic agent. The proposed framework opens up a new avenue of research for investigating mechanistic aspects of ZnO particle adsorption in vitro through long term imaging. Keywords: Fluorescent ZnO particle, Time-lapse microscopy, 3D Live-cell imaging, laser scanning confocal microscope, Reactive oxygen species

The global pandemic outbreak, SARS-COV-2, which causes COVID-19, has coerced numerous pharmaceutical companies to sprint for the vaccine and therapeutic biologics development. Most of the therapeutic biologics are common human IgG antibodies, which were identified by next-generation sequencing with the B cells from the convalescent patients in less than one-month post-infection. While the global public health emergency calls for medications urgently, it saves lives to expedite the clinical trials of biologics as much as possible, hence the biologics development strategies are unprecedentedly challenged. Since the advent of therapeutic biologics, transfection, and selection strategy has been continuously improving for developing more robust cell lines with greater productivity and efficiency. Next-generation sequencing (NGS) has also been implemented into cell bank testing for acceleration. These recent advances enable us to rethink and reshape the chemistry, manufacturing and controls (CMC) strategy against the pandemic outbreaks, to start supplying cGMP materials for the life-saving clinical trials as soon as possible. We elucidated an accelerated CMC workflow for biologics against pandemics, including using cGMP-compliant pool materials for Phase I clinical trials, selecting the final clone with similar product quality as Phase I materials for late-stage development and commercial production and matching product quality among different manufacturing stages.

In modeling cell culture growth using unstructured model, two types of equations are normally used: logistic and Monod. However, these two equations are known for their limitations to model death phase of cell culture growth and to account for dead cells accumulation data. In this paper, we present a modeling framework whereby both Logistic and Monod equations can be used in a single set of equations system to overcome these limitations. First, it can be shown that the increase of total cell population that consists of viable and dead cells follows a logistic growth pattern with its own intrinsic growth rate and total carrying capacity. Furthermore, a hybrid Logistic-Monod equation with first-order decay kinetics can be used to model viable cell growth data with decline phase effectively. With this paradigm, a pseudo-rate equation can be written to account for dead cells accumulation data using population balancing with a simple understanding that dead cell population is simply the difference between total and viable cells. These equations can be adjoined with substrate consumption and product generation rate equations to depict complete batch growth data that covers exponential growth and death phases. This modeling framework has been fitted successfully to fit batch growth data of two cell lines from published literature with complete depictions of dead cell accumulation and cell viability profiles. The implication of this modeling framework for chemostat culture performance analysis is further investigated. 

Plant biomass constitutes the main resource of renewable carbon in the planet and its valorization has traditionally been focused on the use of cellulose, although hemicellulose is the second most abundant group of polysaccharides on earth. Enzymes involved in its degradation are usually glycosyl hydrolases and filamentous fungi are good producers of these enzymes. In this study, a new strain of Aspergillus niger was utilized for hemicellulase production under solid state fermentation using wheat straw as a single carbon source. Physicochemical parameters for production of an endoxylanase were optimized by using one factor at a time approach and response surface methodology (RSM). Maximum xylanase yield after RSM optimization was increased 3-fold. The enzyme was purified by ultrafiltration and ion-exchange chromatography1.41-fold, with 6.2 % yield. Highest xylanase activity was observed at 50 °C and pH 6. A high pH and thermal stability were found, greater than 90% residual activity between pH 3.0-9.0 and between 30-40°C, after 24 h of incubation, presenting half-lives of 30 min at 50 and 60°C. Enzyme was mostly active for wheat arabinoxylan, and displayed the following kinetic parameters Km of 26.06 mg•ml-1 and Vmax of 5,647 U•mg-1min-1.Wheat straw xylan hydrolysis with the purified β-1,4 endoxylanase showed that it was able to release xylooligosaccharides, making it suitable for different applications in food technology.

Steviol glycosides, mostly extracted from Stevia rebaudiana Bertoni, are non-caloric, safe natural sweeteners. Steviosides make up more than 50% of total steviol glycosides but possess a bitter aftertaste, which limits their application as food additives. Trace amounts of rubusosides are acceptable sweeteners, but their supply is limited. In this study, we screened an endophytic bacteria (Lelliottia LST-1) that can specifically convert stevioside into rubusoside and reach a conversion rate of 75.4% after response surface optimization. Potential β-glucosidases GH3-1, GH3-2, GH3-3, and GH3-4 based on whole genome sequencing were expressed and interacted with steviol glycosides to explore principle and process of biological transformation. High-performance liquid chromatography revealed that all enzymes hydrolyzed stevioside and generated rubusoside, but substrate specificity analysis indicated that GH3-2 is the most suitable choice for the durative, steady, and high-efficiency production of rubusoside

Fed-batch culture currently represents the typical choice for the production of monoclonal antibodies (mAbs) in the biopharmaceutical industry. However, the implementation of perfusion culture process combined with continuous manufacturing has gained attention due to increased productivity and resource savings. In this paper, we compared the host cell protein (HCP) production and profile of mAb1 between fed-batch and perfusion culture processes. Our work demonstrated differences in HCP production based on the type of cell culture process for the first time. We focused on HCPs that get carried through the purification process and are present in the final drug substance at levels impacting antibody quality and stability. Perfusion process had lower HCP levels and enabled higher clearance of problematic HCPs compared to fed-batch suggesting a viable alternative process. Furthermore, our work demonstrates proof of concept of the impact of cell culture process on specific product quality and help to navigate the process design when we move from traditional fed-batch to next-generation perfusion cell culture.

Chinese hamster ovary (CHO) is the most commonly used host cell line for therapeutic protein production. Their exposure to highly concentrated feed solution during fed-batch cultivation can cause an unphysiological osmolality increase (>300 mOsm/kg) affecting cell physiology, morphology, and proteome. In a companion article “Hyperosmolality in CHO Culture: Effects on Cellular Behavior and Morphology” we show that hyperosmolalities of up to 545 mOsm/kg force cells to ablate proliferation and gradually increase their volume, almost triplicating it. CHO cells also exhibit a significant hyperosmolality-dependent mitochondrial activity increase. To get a deeper insight into molecular mechanisms involved in these processes, we performed a comparative quantitative label-free proteome study of hyperosmolality-exposed vs. control CHO cells. Our analysis revealed key differentially expressed proteins mediating mitochondrial activation, oxidative stress amelioration, and cell cycle progression. We also discovered a previously unknown strong regulation of proteins altering cell membrane rigidity and permeability. Among others, we detected three members of septins, filamentous proteins forming diffusion barriers in the cell, to be highly upregulated in response to hyperosmolality. Taken together, our observations correlate well with the recent CHO-based fluxome and transcriptome studies and expose new unknown targets involved in response to hyperosmotic pressure in mammalian cells.

293T suspensions cells were first cultured in a big bubble-stirred bioreactors for large-scale lentivirus vectors (LV) production in the study. Direct domesticated approaches were utilized for 293 suspensions cells. We validated of the ability to LV package and drew a growth curve in shake flask. The results show 293T suspension culture was successful, and also retained the capacity for LV production. After facile optimization of the viral package and cryopreservation conditions, 293T suspension cells were inoculated in a 5.5 L bioreactor. Packaged CAR-CD30 lentivirus yield was close to that from the original shake flask culture. Cultivation for 4 days in the bioreactor enabled production of 1.5±0.3×107 TU/mL coarse LV and the lentiviral infection efficiency was 48.6±2.8% in T Cells. The process has merits of low cost as well as more effective, and expected to be highly competitive compared to other bioreactors.

Endoglucanases are necessary to improve high-solids enzymatic hydrolysis of lignocellulosic biomass by promoting liquefaction and decreasing the medium viscosity, alleviating one of the processes’ major hindrances. In this study, endoglucanases produced by a particular strain of Aspergillus awamori were evaluated to speed up biomass liquefaction in reactions with 30% solids. Firstly, A. awamori crude supernatant (Aa) was assessed as a supplement to commercial enzymes, decreasing the media viscosity in 10-fold and improving glucose release by 20% after 24 h. Afterward, Aa was fractionated by size-exclusion chromatography and an endoglucanases-rich fraction was identified by liquid chromatography-mass spectrometry. This fraction was then supplemented to the most efficient commercial enzyme and its performance compared with the unfractionated Aa, resulting in the same improvement on medium viscosity and glucose release in 6 h. These data indicate that A. awamori endoglucanases have a powerful effect on the viscosity decrease during high-solids enzymatic hydrolysis.

Sophorolipids (SLs) are regarded as one of the most promising biosurfactants. They have a low toxicity and are easily degradable without polluting the environment. However, high production costs are the main obstacle to extended SLs application. Semi-continuous fermentation is a promising technology for achieving high SLs productivity, which is based on in-situ separation. In this study, the sedimentation mechanism of SLs was analyzed. The formation of a hydrophobic mixture of SLs and oil was a key factor in sedimentation. The hydrophobicity and density of the mixture determined SLs sedimentation rate. According to the mechanism, ultrasonic enhanced sedimentation technology (UEST) was introduced, by which the sedimentation rates were increased by 46.9% to 485.4% with different Oil/SLs ratios. UEST-assisted real-time rational in-situ separation and semi-continuous fermentation were performed. We observed that SLs productivity and yield were 2.15 g/L and 0.58 g/g, whereas the loss ratio of cells, glucose, and oil was reduced by 68.2%, 16.2%, and 65.5%, respectively. In-situ SLs separation efficiency and rate were increased by 34.5% and 26.4%, respectively. This study provides the foundation and new horizon for the optimization of the SLs fermentation process.

(S)-Omeprazole is a very effective anti-ulcer medicine, and it is a significant challenge to prepare it by whole cells and to substantially increase the substrate concentration. In the chloroform–water biphasic system, resting cells of the mutant of Rhodococcus rhodochrous(R. rhodochrous)ATCC 4276 were employed to catalyze the bio-oxidation of the omeprazole sulfide for preparation of (S)-omeprazole. At a high substrate concentration(180 mM) and cell concentration(100 g/L), the bio-oxidation was optimized using response surface methodology(RSM), and the optimal yield of (S)-omeprazole obtained was 92.9% with enantiomeric excess(e.e.) (>99%), and no sulfone product was detected under the optimal conditions: the reaction temperature was 37°C, pH of phosphate buffer, 7.3 and the reaction time, 43h respectively. A quadratic polynomial model was established, which predicts the experimental data with very high accuracy according to R2 of 0.9990. The chloroform–water biphasic system may mainly contribute the significant improvement of substrate tolerance because almost all substrates may partitioned in the organic phase (water solubility of omeprazole sulfide is only about 0.5 mg/ml), resulting in little damage and inhibition to cells by substrates. The mutant of R. rhodochrous ATCC 4276 exhibited a high enantioselective, activity and substrate and product tolerance. The aerated flask provides enough oxygen for a high concentration of cells. Accordingly, the bio-oxidation is thus more promising for efficient preparation of chiral sulfoxides.

Co-degradation of coal and straw could produce significantly higher methane which was potential to increase biogenic CBM. In this study, the success of microflora and organic compounds during co-degradation was determined by MiSeq and GC-MS, and compared with cultivations with only coal (C) and with only straw (RS). The results showed that the methane production in co-degradation was 12 times higher than that in cultivation C. A shift of dominant methanogen was caused by the addition of straw from acetoclastic Methanosaeta in inoculum to methylotrophic Methanomethylovorans in 7 days, then hydrogenotrophic Methanobacterium. The bacteria and fungi with ability to degrade macromolecules in coal and metabolize VFAs were enriched which would facilitate methanogenesis. VFAs, especially butanoic acid, were dominant in intermediates of co-degradation which contributed to methane production as their content were negatively corelated with methane production. The different component of intermediates and microbial communities among co-degradation, cultivations C and RS suggested that the metabolic pathway in co-degradation was distinctive and the fracture of coal molecules was almost completed in the first 7 days of cultivation. Coal might also serve as the suitable microhabitat for microorganisms to avoid the threat from environment in addition to function as methanogenic substrates.