Biopharmaceutical protein production using transgenic plant cell bioreactor processes offers advantages over microbial and mammalian cell culture platforms due to the ability to produce complex biologics, use of simple chemically-defined, animal component-free media, robustness of host cells, and biosafety. A disadvantage of plant cells from a traditional batch bioprocessing perspective is their slow growth rate which has motivated us to develop semicontinuous and/or perfusion processes. Although the economic benefits of plant cell culture bioprocesses are often mentioned in the literature, to our knowledge no rigorous techno-economic models or analyses have been published. Here we present techno-economic models in SuperPro Designer® for the large-scale production of recombinant butyrylcholinesterase (BChE), a prophylactic/therapeutic bioscavenger against organophosphate nerve agent poisoning, in inducible transgenic rice cell suspension cultures. The base facility designed to produce 25 kg BChE per year utilizing two-stage semicontinuous bioreactor operation manufactures a single 400 mg dose of BChE for $263. Semicontinuous operation scenarios result in 4-11% reduction over traditional two-stage batch operation scenarios. In addition to providing a simulation tool that will be useful to the plant-made pharmaceutical community, the model also provides a computational framework that can be used for other semicontinuous or batch bioreactor-based processes.
We report on the development of a new model of alveolar air-tissue interface consisting of an array of suspended hexagonal monolayers of gelatin nanofibers supported by microframes and a microfluidic device for the patch integration. The suspended monolayers are deformed to a central displacement of 40-80 μm at the air-liquid interface by application of air pressure in the range of 200-1000 Pa. With respect to the diameter of the monolayers that is 500 μm, this displacement corresponds to a linear strain of 2-10% in agreement with the physiological strain range in the lung alveoli. The culture of A549 cells on the monolayers for an incubation time 1-3 days showed viability in the model. We exerted a periodic strain of 5% at a frequency of 0.2 Hz during 1 hour to the cells. We found that the cells were strongly coupled to the nanofibers, but the strain reduced the coupling and induced remodeling of the actin cytoskeleton, which led to a better tissue formation. Our model can serve as a versatile tool in lung investigations such as in inhalation toxicology and therapy.
Homologous recombination over large genomic regions is difficult to achieve due to low efficiencies. Here, we report the successful engineering of a humanized mTert allele, hmTert, in the mouse genome by replacing an 18.1-kb genomic region around the mTert gene with a recombinant fragment of over 45.5-kb, using homologous recombination facilitated by the Crispr/Cas9 technology, in mouse embryonic stem cells (mESCs). In our experiments, with specific sites of DNA double strand breaks (DSBs) by Crispr/Cas9 system, the homologous recombination efficiency was up to 11% and 16% in two mESC lines TC1 and v6.5, respectively. Overall, we obtained a total of 27 mESC clones with heterozygous hmTert/mTert alleles and 3 clones with homozygous hmTert alleles. DSBs induced by Crispr/Cas9 cleavages also caused high rates of genomic DNA deletions and mutations at small guide RNA (sgRNA) target sites. Our results indicated the Crispr/Cas9 system significantly increased the efficiency of homologous recombination-mediated gene editing over a large genomic region in mammal cells, but also inherently caused mutations at unedited target sites. Overall, this strategy provides an efficient and feasible way for manipulating large chromosomal regions.
Clinical use of pancreatic beta islets for regenerative medicine applications requires mass production of functional cells. Current technologies are insufficient for large-scale production in a cost-efficient manner. Here, we evaluate advantages of a porous cellulose scaffold and demonstrate scale-up to a wicking-matrix bioreactor as a platform for culture of human endocrine cells. Scaffold modifications were evaluated in a multi-well platform to find the optimum surface condition for pancreatic cell expansion followed by bioreactor culture to confirm suitability. Preceding scale-up, cell morphology, viability and proliferation of primary pancreatic cells were evaluated. Two optimal surface modifications were chosen and evaluated further for insulin secretion, cell morphology and viable cell density for human induced pluripotent stem cell-derived pancreatic cells at different stages of differentiation. Scale-up was accomplished with uncoated, amine-modified cellulose in a miniature bioreactor, and insulin secretion and cell metabolic profiles were determined for 13 days. We achieved 10-fold cell expansion in the bioreactor along with a significant increase in insulin secretion compared with cultures on tissue-culture plastic. Our findings define a new method for expansion of pancreatic cells on wicking-matrix cellulose platform to advance cell therapy biomanufacturing for diabetes.
The rare ginsenosides are recognized as the functionalized molecules after oral administration of Panax ginseng and its products. The sources of rare ginsenosides are extremely limited because of low ginsenoside contents in wild plants, hindering their application in functional foods and drugs. We developed an effective combinatorial biotechnology approach including tissue culture, immobilization, and hydrolyzation methods. Rh2 and nine other rare ginsenosides were produced by MeJA-induced culture of adventitious roots in a 10 L bioreactor associated with enzymatic hydrolysis using six β-glycosidases and their combination with yields ranging from 5.54-32.66 mg L-1. The yield of Rh2 was furthermore increased 7% by using immobilized BglPm and Bgp1 in optimized pH and temperature condition, with the highest yield reaching 51.17 mg L-1 (17.06% of PPD-type ginsenosides mixture). Our combinatorial biotechnology method provides a highly efficient approach to acquiring diverse rare ginsenosides, replacing direct extraction from Panax plants, and can also be used to supplement yeast cell factories.
In recent years, bacteria from genus Clostridia have attracted attention of research community because of their biofuel production capabilities. Present study reports comparative genomic (CG) analysis of 48 genomes of solventogenic and saccharolytic Clostridia. We have focused on central carbon metabolism and general stress response in the analysis. Comprehensive summaries on comparison of general genome features, COG categories, CDSs of the energy, catabolic, and sporulation pathways are given. Furthermore, we have proposed two new genome-scale metabolic (GSM) models iKK848 and iKK1425 for Clostridium pasteurianum DSM 525 = ATCC 6013 and Clostridium acetobutylicum ATCC 824, respectively. These GSM models are most comprehensive in that they account for the largest number of reactions, metabolites, and genes as compared to previous models. Model quality and metabolic flux optimization for biomass growth using iKK1425 and iKK848 are compared with previous literature. Our models had the highest quality score of 61% and 77%.
The rapidly expanding market for regenerative medicines and cell therapies highlights the need to advance the understanding of cellular metabolisms and improve the prediction of cultivation production process for human induced pluripotent stem cells (iPSCs). In this paper, a metabolic kinetic model was developed to characterize underlying mechanisms of iPSC culture process, which can predict cell response to environmental perturbation and support process control. This model focuses on the central carbon metabolic network, including glycolysis, pentose phosphate pathway (PPP), tricarboxylic acid (TCA) cycle, and amino acid metabolism, which plays a crucial role to support iPSC proliferation. Heterogeneous measures of extracellular metabolites and multiple isotopic tracers collected under multiple conditions were used to learn metabolic regulatory mechanisms. Systematic cross-validation confirmed the model’s performance in terms of providing reliable predictions on cellular metabolism and culture process dynamics under various culture conditions. Thus, the developed mechanistic kinetic model can support process control strategies to strategically select optimal cell culture conditions at different times, ensure cell product functionality, and facilitate large-scale manufacturing of regenerative medicines and cell therapies.
Fermentation monitoring is a powerful tool for bioprocess development and optimisation. On-line metabolomics is a technology that is starting to gain attention as a bioprocess monitoring tool, allowing the direct measurement of many compounds in the fermentation broth at a very high time resolution. In this work, targeted on-line metabolomics was used to monitor 40 metabolites of interest during three Escherichia coli succinate production fermentation experiments every 5 minutes with a triple quadrupole mass spectrometer. This allowed capturing high time resolution biological data that can provide critical information for process optimisation. For 9 of these metabolites, simple univariate regression models were used to model compound concentration from their on-line mass spectrometry peak area. These on-line metabolomics univariate models performed comparably to vibrational spectroscopy multivariate PLS regressions models reported in the literature, which typically are much more complex and time consuming to build. In conclusion, this work shows how on-line metabolomics can be used to directly monitor many bioprocess compounds of interest and obtain rich biological and bioprocess data.
The recent uptick in the approval of ex vivo cell therapies highlight the relevance of Lentivirus (LV) as an enabling viral vector of modern medicine. As labile biologics, however, LVs pose critical challenges to industrial biomanufacturing. In particular, LV purification – currently reliant on filtration and anion-exchange or size-exclusion chromatography – suffers from long process times and low yield of transducing particles, which translate in high waiting time and cost to patients. Seeking to improve LV downstream processing, this study introduces peptides targeting the enveloped protein Vesicular stomatitis virus G (VSV-G) to serve as affinity ligands for the chromatographic purification of LV particles. An ensemble of candidate ligands was initially discovered by implementing a dual-fluorescence screening technology and a targeted in silico approach designed to identify sequences with high selectivity and tunable affinity. The selected peptides were conjugated on Poros resin and their LV binding-and-release performance was optimized by adjusting the flow rate, composition, and pH of the chromatographic buffers. Ligands GKEAAFAA and SRAFVGDADRD were selected for their high product yield (50-60% of viral genomes; 40-50% of HT1080 cell-transducing particles) upon elution in PIPES buffer with 0.65 M NaCl at pH 7.4. The peptide-based adsorbents also presented remarkable values of binding capacity (up to 3·10 9 TU per mL of resin at the residence time of 1 min) and clearance of host cell proteins (up to 220-fold reduction of HEK293 HCPs). Additionally, GKEAAFAA demonstrated high resistance to caustic cleaning-in-place (0.5 M NaOH, 30 min) with no observable loss in product yield and quality.
In recent years, environmental DNA (eDNA) has received attention from biologists due to its sensitivity, convenience, labor and material efficiency, and lack of damage to organisms. The extensive application of eDNA has opened avenues for the monitoring and biodiversity assessment of amphibians, which are frequently small and difficult to observe in the field, in areas such as biodiversity survey assessment and detection of specific, rare and endangered, or alien invasive species. However, the accuracy of eDNA can be influenced by factors such as ambient temperature, pH, and false positives or false negatives, which makes eDNA an adjunctive tool rather than a replacement for traditional surveys. This review provides a concise overview of the eDNA method and its workflow, summarizes the differences between applying eDNA for detecting amphibians and other organisms, reviews the research progress in eDNA technology for amphibian monitoring, identifies factors influencing detection efficiency, and discusses the challenges and prospects of eDNA. It aims to serve as a reference for future research on the application of eDNA in amphibian detection.
Hollow fiber-based membrane filtration has emerged as the dominant technology for cell retention in perfusion processes yet significant challenges in alleviating filter fouling remain unsolved. In this work, the benefits of co-current filtrate flow applied to a tangential flow filtration (TFF) module to reduce or even completely remove Starling recirculation caused by the axial pressure drop within the module was studied by pressure characterization experiments and perfusion cell culture runs. Additionally, a novel concept to achieve alternating Starling flow within unidirectional TFF was investigated. Pressure profiles demonstrated that precise flow control can be achieved with both lab-scale and manufacturing scale filters. TFF systems with co-current flow showed up to 40% higher product sieving compared to standard TFF. The decoupling of transmembrane pressure from crossflow velocity and filter characteristics in co-current TFF alleviates common challenges for hollow-fiber based systems such as limited crossflow rates and relatively short filter module lengths, both of which are currently used to avoid extensive pressure drop along the filtration module. Therefore, co-current filtrate flow in unidirectional TFF systems represents an interesting and scalable alternative to standard TFF or alternating TFF operation with additional possibilities to control Starling recirculation flow.
With the further improvement of food safety requirements, the development of fast, high sensitivity, and portability methods for the determination of foodborne hazardous substances has become a new trend in the food industry. In recent years, biosensors and platforms based on functional nucleic acids and a range of signal amplification devices and methods have been established to allow rapid and sensitive determination of specific substances in samples by different methods, opening up a new avenue of analysis and detection. In this paper, functional nucleic acid types including aptamers, deoxyribozymes and G-quadruplexes which are commonly used in the detection of food source pollutants are mainly introduced, as well as nano signal amplification elements including quantum dots, noble metal nanoparticles, magnetic nanoparticles, DNA walkers, DNA logic gates. signal amplification technologies including nucleic acid isothermal amplification, HCR, CHA, biological barcode, and microfluidic system are combined with functional nucleic acid sensors and applied to the detection of many foodborne hazardous substances, such as foodborne pathogens, mycotoxins, residual antibiotics, residual pesticides, industrial pollutants, heavy metals, and allergens.Finally, the potential opportunities and broad prospects of functional nucleic acid biosensors in the field of food analysis are discussed.
Researchers and engineers came together in Lisbon at the 27 th Meeting of the European Society for Animal Cell Technology (ESACT 2022), to discuss the latest advances in technologies associated with protein-based biologics production, new modalities and cell, gene and tissue therapies. Main contributions focused on how the capabilities of production platforms can be enhanced, and how to leverage them to generate new products. Some of the advances that were presented are discussed below, including those related with cell line development, metabolic engineering, analytics, CHO and insect cells platforms engineering, vesicle and viral vector production, and gene and cell therapy, along with some concluding remarks on the future of this important field.
Zymomonas mobilis is an emerging chassis for being engineered to produce bulk products due to its glycolysis through the Entner-Doudoroff pathway with less ATP produced for lower biomass accumulation and higher yields with targeted products. When self-flocculated, the bacterial cells are more productive and tolerant to stresses for high product titers, but this morphology needs to be controlled properly to avoid internal mass transfer limitation associated with strong flocculation. Herewith we explored the regulation of cyclic diguanosine monophosphate (c-di-GMP) on self-flocculation of the bacterial cells through cellulose biosynthesis. While ZMO1365 and ZMO0919 with GGDEF domains for diguanylate cyclase activities catalyze c-di-GMP biosynthesis, ZMO1487 with an EAL domain for phosphodiesterase activities catalyzes c-di-GMP degradation, but ZMO1055 and ZMO0401 contain the dual domains with phosphodiesterase activities predominated. Since c-di-GMP is synthesized from GTP, the intracellular accumulation of this signal molecule through deactivating the activity of phosphodiesterase is preferred for activating cellulose biosynthesis to flocculate the bacterial cells, since such a strategy exerts less perturbance on intracellular processes regulated by GTP. These discoveries are significant not only for engineering unicellular Z. mobilis strains with the self-flocculating morphology to boost production, but also for understanding mechanism underlying c-di-GMP biosynthesis and degradation in the bacterium.
Pichia pastoris ( Komagataella phaffii) is a fast-growing methylotrophic yeast with the ability to assimilate several carbon sources such as methanol, glucose, or glycerol. It has been shown to have outstanding secretion capability with a variety of heterologous proteins. In previous studies, we engineered P. pastoris to co-express E. coli AppA phytase and the HAC1 transcriptional activator using a bidirectional promoter. Phytase production was characterised in shake flasks and did not reflect industrial conditions. In the present study, phytase expression was explored and optimised using instrumented fermenters in continuous and fed-batch modes. First, the production of phytase was investigated under glucose de-repression in continuous culture at three dilution factors, 0.5 d -1, 1 d -1, and 1.5 d -1. The fermenter parameters of these cultures were used to inform a kinetic model in batch and fed-batch modes for growth and phytase production. The kinetic model developed aided to design the glucose feeding profile of a fed-batch culture. Kinetic model simulations under glucose de-repression and fed-batch conditions identified an optimal phytase productivity at the specific growth rate of 0.041 h -1. Validation of the model simulation with experimental data confirmed the feasibility of the model to predict phytase production in our newly engineered strain. Methanol was used only to induce the expression of phytase at high cell densities. Our results showed that high phytase production required two stages, the first stage used glucose under de-repression conditions to generate biomass while expressing phytase, and stage two used methanol to induce phytase expression. The production of phytase was improved 3.5-fold by methanol induction compared to the expression with glucose alone under de-repression conditions to a final phytase activity of 12.65 MU/L. This final volumetric phytase production represented an approximate 36-fold change compared to the flask fermentations. This two-phase strategy allowed to optimise phytase productivity by producing phytase during both growth and methanol induction phases. Finally, the phytase protein produced was assayed to confirm its molecular weight, and pH and temperature profiles. This study highlights the importance of optimising protein production in P. pastoris when using novel promoters and presents a general approach to performing bioprocess optimisation in this important production host.
Current manufacturing and development processes for therapeutic monoclonal antibodies demand increasing volumes of analytical testing for both real-time process controls and high-throughput process development. The feasibility of using Raman spectroscopy as an in-line product quality measuring tool has been recently demonstrated and promises to relieve this analytical bottleneck. Here, we resolve manual calibration effort by engineering an automation system capable of collecting Raman spectra on the order of hundreds of calibration points from two to three stock seed solutions using controlled mixing. We used this automated system to calibrate multi-product quality attribute models that accurately measured product concentration and aggregation every 9.3 seconds using an in-line flow-cell. We demonstrate the application of a non-linear calibration model for monitoring product quality in real-time during a biopharmaceutical purification process intended for clinical and commercial manufacturing. These results demonstrate potential feasibility to implement quality monitoring during GMP manufacturing as well as to increase CMC understanding during process development, ultimately leading to more robust and controlled manufacturing processes.
The methodology for production of biologics is going through a paradigm shift from batch-wise operation to continuous production. Lot of efforts are focused on integration, intensification and continuous operation for decreased foot-print, material, equipment and increased productivity and product quality. These integrated continuous processes with on-line analytics becomes complex processes, which requires automation, monitoring and control of the operation, even unmanned or remote, which means bioprocesses with high level of automation or even autonomous capabilities. The development of these digital solutions becomes an important part of the process development and needs to be assessed early in the development chain. This work discusses a platform that allow fast development, advanced studies and validation of digital solutions for integrated continuous downstream processes. It uses an open, flexible and extendable real-time supervisory controller, called Orbit, developed in Python. Orbit makes it possible to communicate with a set of different physical setups and on the same time perform real-time execution. Integrated continuous processing often imply parallel operation of several setups and network of Orbit controllers makes it possible to synchronize complex process system. Data handling, storage and analysis are important properties for handling heterogeneous and asynchronous data generated in complex downstream systems. Digital twin applications, such as advanced model-based and plant-wide monitoring and control, are exemplified using computational extensions in Orbit, exploiting data and models. Examples of novel digital solutions in integrated downstream processes are automatic operation parameter optimization, Kalman filter monitoring and model-based batch-to-batch control.
The biopharmaceutical industry is still running in batch mode, mostly because it is a highly regulated industry sector. In the past, sensors were not readily available and in-process control was mainly executed off-line. The most important product parameters are quantity, purity and potency besides adventitious agents and bioburden. There is increasing economic pressure on time-to-market and also on the environmental sustainability of biopharmaceutical manufacturing. New concepts for manufacturing using disposable single-use technologies and integrated bioprocessing will dominate the future of bioprocessing. In order to ensure the quality of pharmaceuticals initiatives such as Process Analytical Technologies, Quality by Design and Continuous Integrated Manufacturing have been established. The vision must be that these initiatives together with technology development pave the way for process automation and autonomous bioprocessing without any human intervention. Then a real-time release would be realized leading to a highly predictive and robust biomanufacturing system. The steps toward such automated and autonomous bioprocessing are reviewed in context of monitoring and control. Starting from statistical treatment of single and multiple sensors, establishing soft sensors with predictive chemometrics and hybrid models. A scenario is described how to integrate soft sensors and predictive chemometrics into modern process control. This will be exemplified by selective downstream processing steps such as chromatography and membrane filtration, the most common unit operations for separation of biopharmaceuticals.