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.
Medical progress as enabled by early plasma products has also revealed biological safety challenges. The combination of donor selection, donation testing and virus reduction processes has effectively addressed these concerns, and today medicinal plasma products feature significant safety margins. The safety tripod concept has since been adapted to biotechnology manufacturing platforms and has also ensured the safety of these products. However, cell-based manufacturing processes have occasionally been exposed to adventitious viruses, leading to manufacturing interruptions and unstable supply situations. The rapid progress of advanced therapy medicinal products (ATMPs) needs an innovative approach to ensure the learnings from more traditional biotechnology help to avoid any unwelcome reminder of the universal presence of viruses. The introduction of up-stream virus clearance steps has already been shown to be valuable for any products too complex for down-stream interventions in the sense of both assuring product safety and continuous supply. The gentlest method being virus filtration – the development of which is presented here. The experiments investigated the feasibility of implementing culture media virus filtration with respect to their virus clearance capacities under extreme conditions such as very high process feed loading (up to ~ 19,000 L/m 2), very long duration (up to 31 days), and multiple process interruptions (up to 21, with cumulative interruptions of over 92 hours). Minute virus of mice (MMV) was used as a relevant target virus, and in general, as a model small non-enveloped virus, as these viruses are the main challenge for the investigated virus filters with a stipulated pore-size of about 20 nm. It was found that certain filters – especially of the newer 2 nd generation – are capable of effective virus clearance despite the harsh regimen they were subjected to. At the same time the investigation of biochemical parameters for un-spiked control runs showed the filters to have no measurable impact on the composition of the culture media. Based on these findings, this technology seems to be quite feasible for large volume pre-manufacturing process culture media preparations.
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.
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.
Chromatographic data processing has garnered attention due to multiple FDA 483 citations and warning letters, highlighting the need for a robust technological solution. The healthcare industry has the potential to greatly benefit from the adoption of digital technologies, but the process of implementing these technologies can be slow and complex. This article presents a “Digital by Design” managerial approach, adapted from pharmaceutical quality by design principles, for designing and implementing an artificial intelligence (AI)-based solution for chromatography peak integration process in the healthcare industry. We report the use of a convolutional neural network model to predict analytical variability for integrating chromatography peaks and propose a potential GxP framework for using artificial intelligence in the healthcare industry that includes elements on data management, model management, and human-in-the-loop processes. The component on analytical variability prediction has a great potential to enable Industry 4.0 objectives on real-time release testing, automated quality control, and continuous manufacturing.
Optimization and monitoring of bioprocesses requires the measurement of several process parameters and quality attributes. Mass spectrometry (MS)-based techniques such as those coupled to gas chromatography (GCMS) and liquid Chromatography (LCMS) enable the simultaneous measurement of hundreds of metabolites with high sensitivity. When applied to spent media, such metabolome analysis can help determine the sequence of substrate uptake and metabolite secretion, consequently facilitating better design of initial media and feeding strategy. Furthermore, the analysis of metabolite diversity and abundance from spent media will aid the determination of metabolic phases of the culture and the identification of metabolites as surrogate markers for product titer and quality. This review covers the recent advances in metabolomics analysis applied to the development and monitoring of bioprocesses. In this regard, we recommend a stepwise workflow and guidelines that a bioprocesses engineer can adopt to develop and optimize a fermentation process using spent media analysis. Finally, we show examples of how the use of MS has revolutionized the design and monitoring of bioprocesses.
In the production of biopharmaceuticals depth filters followed by sterile filters are often employed to remove residual cell debris present in the feed stream. In the back drop of a global pandemic, supply chains associated with the production of biopharmaceuticals have been constrained. These constraints have limited the available amount of depth filters for the manufacture of biologics. This has placed manufacturing facilities in a difficult position having to choose between running processes with reduced number of depth filters and risking a failed batch or the prospect of plants going into temporary shutdown until the depth filter resources are replenished. This communication describes a modeling based method that leverages manufacturing scale filtration data to predict the depth filter performance with a reduced number of filters and an increased operational flux. This method can be used to quantify the acceptable level of area reduction before which the filtration process performance is affected. This enables facilities to manage their filter inventory avoiding potential plant shutdowns and reduces the risks of negative depth filter performance.
There are few reports of the adoption of continuous processes in bioproduction, particularly the implementation of end-to-end continuous processes, due to difficulties such as feed adjustment, production batch demarcation, and incorporating virus filtration. Here, we propose an end-to-end continuous process for a monoclonal antibody (mAb) with three integrated process segments: upstream production processes with pool-less direct connection, pooled low pH virus inactivation with automated pH control and a total flow-through integrated polishing process in which two columns were directly connected with a virus filter. The pooled virus inactivation step demarcates the batch, and high impurities reduction and mAb recovery were achieved for batches conducted in succession. Viral clearance tests also confirmed robust virus reduction for the flow-through two column chromatography and the virus filtration steps. Additionally, viral clearance tests with two different hollow fiber virus filters operated at flux ranging from 1.5 to 40 LMH confirmed robust virus reduction over these ranges. Complete clearance with LRV ≥ 4 was achieved even with a process pause at the lowest flux. The end-to-end continuous process proposed in this study is highly applicable to production processes, and the investigated virus filters have excellent applicability to continuous processes conducted at constant flux.
Adeno-associated viruses (AAVs) are the vector of choice for delivering gene therapies that can cure inherited and acquired diseases. Clinical research on various AAV serotypes significantly increased in recent years alongside regulatory approvals of AAV-based therapies. The current AAV purification platform hinges on the capture step, for which several affinity resins are commercially available. These adsorbents rely on protein ligands – typically camelid antibodies – that provide high binding capacity and selectivity, but suffer from low biochemical stability and high cost, and impose harsh elution conditions (pH < 3) that can harm the transduction activity of recovered AAVs. Addressing these challenges, this study introduces peptide ligands that selectively capture AAVs and release them under mild conditions (pH 6.0). The peptide sequences were identified by screening a focused library and modeled in silico against AAV serotypes 2 and 9 (AAV2 and AAV9) to select candidate ligands that target homologous sites at the interface of the VP1-VP2 and VP2-VP3 virion proteins with mild binding strength (K D ~ 10 -5-10 -6 M). Selected peptides were conjugated to Toyopearl resin and evaluated via binding studies against AAV2 and AAV9, demonstrating the ability to target both serotypes with values of dynamic binding capacity (DBC 10% > 10 13 vp per mL of resin) and product yields (~50-80%) on par with commercial adsorbents. The peptide-based adsorbents were finally utilized to purify AAV2 from a HEK 293 cell lysate, affording high recovery (50-80%), 80-to-400-fold reduction of host cell proteins (HCPs), and high transduction activity (up to 80%) of the purified viruses.
Nonwoven membranes are highly engineered fibrous materials that can be manufactured on a large scale from a wide range of different polymers, and their surfaces can be modified using a large variety of different chemistries and ligands. The fiber diameters, surface areas, pore sizes, total porosities, and thicknesses of the nonwoven mats can be carefully controlled, providing many opportunities for creative approaches for the development of novel membranes with unique properties to meet the needs of the future of downstream processing. Fibrous membranes are already finding use in ultrafiltration, microfiltration, depth filtration, and, more recently, in membrane chromatography for product capture and impurity removal. This article summarizes the various methods of manufacturing nonwoven fabrics, and the many methods available for the modification of the fiber surfaces. It also reviews recent studies focused on the use of nonwoven fabric devices in membrane chromatography and provides some perspectives on the challenges that need to be overcome to increase binding capacities, decrease residence times, and reduce pressure drops so that eventually they can replace resin column chromatography in downstream process operations.
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.
Pre-packed chromatography columns and cassette filtration units offer many advantages in bioprocessing. These include reduced labor costs and processing times, ease of storage, and enhanced process flexibility. Rectangular formats are particularly attractive as they can be stacked and multiplexed together for continuous processing. Cylindrical chromatography beds have historically been favored even though their bed support and pressure-flow performance vary with bed dimensions. This work presents the performance of rectangular chromatography devices with novel internally supported beds. They are compatible with existing chromatography workstations and can be packed with any standard commercial resin. The devices offer pressure-flow characteristics independent of container-volume, simple multiplexing, and separation performance comparable to cylindrical columns. Their internal bed support allows mechanically less-rigid resins to be used at up to 4 times higher maximal linear velocities, and productivities approaching 200 g/L/h for affinity resins, compared to the 20 g/L/h typical of many column-based devices. Three 5 L devices should allow processing of up to 3 kg of monoclonal antibody per hour.
Genome-scale metabolic models (GSMMs) and flux balance analysis (FBA) have been extensively used to model and design bacterial fermentation. However, FBA-based metabolic models designed for simulating the dynamics of co-culture with quantitative accuracy are still uncommon, which is particularly true for lactic acid bacteria (LAB) used for yogurt fermentation. To investigate metabolic interactions in yogurt starter culture of Streptococcus thermophilus (ST) and Lactobacillus delbrueckii subsp. bulgaricus (LB), this study built a dynamic community-level GSMM based on metagenomic analysis. We first assessed the accuracy of the model by comparing predicted bacterial growth, consumption of lactose and production of lactic acid with reference experimental data, and then used it to predict the impact of different initial ST:LB inoculation ratios (gDW/gDW) on acidification. The dynamic simulation demonstrated the mutual dependence of ST and LB during the yogurt fermentation process. The modeling pipeline presented in this work provided a basis for the computer-aided process design and control of the production of fermented dairy products, contributing to the development of precision fermentation in the food industry.
Viral vectors for gene therapy, such as recombinant Adeno-Associated Viruses (rAAV), are produced in Human Embryonic Kidney (HEK) 293 cells. However, the presence of the SV40 T-antigen-encoding CDS SV40GP6 and SV40GP7 in the HEK293T genome raises safety issues when these cells are used in manufacturing for clinical purposes. We developed a new T-antigen-negative HEK cell line from ExcellGene’s proprietary HEKExpress®, using the CRISPR-Cas9 strategy. We obtained a high number of clonally-derived cell populations and all of them were demonstrated T-antigen negative. Stability study and AAV production evaluation showed that the deletion of the T-antigen-encoding locus did not impact neither cell growth nor viability nor productivity. The resulting CMC-compliant cell line, named HEKzeroT®, is able to produce high AAV titers, from small to large scale.
Oxygen and extracellular matrix (ECM)-derived biopolymers play vital roles in regulating many cellular functions in both the healthy and diseased liver. This study reveals the importance of synergistically tuning the internal microenvironment to enhance oxygen availability alongside phenotypic ECM ligand presentation to promote native metabolic functions of human liver three-dimensional (3D) cell aggregates. First, fluorinated (PFC) chitosan microparticles (MPs) were generated with a microfluidic chip, then their oxygen transport properties were studied using a custom ruthenium-based oxygen sensing approach. Next, to allow for integrin engagements the surfaces of these MPs were functionalized using liver ECM proteins including fibronectin, laminin-111, laminin-511, and laminin-521. These MPs were used to assemble heterogeneous composite spheroids composed of human hepatocytes and human hepatic stellate cells. After in vitro culture, liver-specific functions and cell adhesion patterns were compared between groups and cells showed enhanced liver phenotypic responses in response to laminin-511 and 521 as evidenced via enhanced E-cadherin and vinculin expression as well as albumin and urea secretion. Furthermore, hepatocytes and stellate cells arranged in more phenotypic arrangements when cocultured with laminin-511 and 521 modified MPs providing clear evidence that specific ECM proteins have distinctive roles in the phenotypic regulation of liver cells in engineering 3D spheroids. This study advances efforts to create more physiologically relevant organ models allowing for well-defined conditions and phenotypic cell signaling which together improve the relevance of 3D spheroid and organoid models.
Chondroitin sulfate A (CSA) is a valuable glycosaminoglycan that has great market demand. However, current synthetic methods are limited by requiring the expensive sulfate group donor 3′-phosphoadenosine-5′-phosphosulfate (PAPS) and inefficient enzyme carbohydrate sulfotransferase 11 (CHST11). Herein, we report the design and integration of the PAPS synthesis and sulfotransferase pathways to realize whole-cell catalytic production of CSA. Using mechanism-based protein engineering, we improved the thermostability and catalytic efficiency of CHST11; its T m and half-life increased by 6.9°C and 3.5 h, respectively, and its specific activity increased 2.1-fold. Via cofactor engineering, we designed a dual cycle strategy of regenerating ATP and PAPS to increase the supply of PAPS. Through surface display engineering, we realized the outer membrane expression of CHST11 and constructed a whole-cell catalytic system of CSA production with a 89.5% conversion rate. This whole-cell catalytic process provides a promising method for the industrial production of CSA.
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.