原位显微镜在细胞生物量在线监测中的发展与应用

随着现代生物技术的快速发展,生物发酵过程在工业生产中的重要性日益增加。为获得质量稳定的发酵产品,通常需要对发酵过程进行监测与调控。生物量可以直接反映生物反应器中细胞代谢的主体——细胞的生长状况,因此实现生物量的在线监测对发酵过程的调控具有重要意义。原位显微镜是一项非侵入式的、基于图像分析的技术,可以实时监测生物过程中的细胞量。文中就原位显微镜的发展及其在细胞生物量实时监测中的应用进行了综述。     

Advances in bioreactor control for production of biotherapeutic products

Advanced control strategies are well established in chemical, pharmaceutical, and food processing industries. Over the past decade, the application of these strategies is being explored for control of bioreactors for manufacturing of biotherapeutics. Most of the industrial bioreactor control strategies apply classical control techniques, with the control system designed for the facility at hand. However, with the recent progress in sensors, machinery, and industrial internet of things, and advancements in deeper understanding of the biological processes, coupled with the requirement of flexible production, the need to develop a robust and advanced process control system that can ease process intensification has emerged. This has further fuelled the development of advanced monitoring approaches, modeling techniques, process analytical technologies, and soft sensors. It is seen that proper application of these concepts can significantly improve bioreactor process performance, productivity, and reproducibility. This review is on the recent advancements in bioreactor control and its related aspects along with the associated challenges. This study also offers an insight into the future prospects for development of control strategies that can be designed for industrial-scale production of biotherapeutic products.     

On-line soft sensing in upstream bioprocessing

This review provides an overview and a critical discussion of novel possibilities of applying soft sensors for on-line monitoring and control of industrial bioprocesses. Focus is on bio-product formation in the upstream process but also the integration with other parts of the process is addressed. The term soft sensor is used for the combination of analytical hardware data (from sensors, analytical devices, instruments and actuators) with mathematical models that create new real-time information about the process. In particular, the review assesses these possibilities from an industrial perspective, including sensor performance, information value and production economy. The capabilities of existing analytical on-line techniques are scrutinized in view of their usefulness in soft sensor setups and in relation to typical needs in bioprocessing in general. The review concludes with specific recommendations for further development of soft sensors for the monitoring and control of upstream bioprocessing.     

Perspectives of fluorescence spectroscopy for online monitoring in microalgae industry

Microalgae industrial production is viewed as a solution for alternative production of nutraceuticals, cosmetics, biofertilizers, and biopolymers. Throughout the years, several technological advances have been implemented, increasing the competitiveness of microalgae industry. However, online monitoring and real-time process control of a microalgae production factory still require further development. In this mini-review, non-destructive tools for online monitoring of cellular agriculture applications are described. Still, the focus is on the use of fluorescence spectroscopy to monitor several parameters (cell concentration, pigments, and lipids) in the microalgae industry. The development presented makes it the most promising solution for monitoring up-and downstream processes, different biological parameters simultaneously, and different microalgae species. The improvements needed for industrial application of this technology are also discussed.     

Model-based monitoring of industrial reversed phase chromatography to predict insulin variants

Downstream processing in the manufacturing biopharmaceutical industry is a multistep process separating the desired product from process- and product-related impurities. However, removing product-related impurities, such as product variants, without compromising the product yield or prolonging the process time due to extensive quality control analytics, remains a major challenge. Here, we show how mechanistic model-based monitoring, based on analytical quality control data, can predict product variants by modeling their chromatographic separation during product polishing with reversed phase chromatography. The system was described by a kinetic dispersive model with a modified Langmuir isotherm. Solely quality control analytical data on product and product variant concentrations were used to calibrate the model. This model-based monitoring approach was developed for an insulin purification process. Industrial materials were used in the separation of insulin and two insulin variants, one eluting at the product peak front and one eluting at the product peak tail. The model, fitted to analytical data, used one component to simulate each protein, or two components when a peak displayed a shoulder. This monitoring approach allowed the prediction of the elution patterns of insulin and both insulin variants. The results indicate the potential of using model-based monitoring in downstream polishing at industrial scale to take pooling decisions.     

An effective automated glucose sensor for fermentation monitoring and control

An industrial glucose analyser was partnered to an automated injection system to evaluate glucose in the culture medium of a bioreactor. This sensor has been validated on continuous cultures ofSchizosaccharomyces pombe and continuous and fed-batch cultures ofSaccharomyces cerevisiae. In addition to the advantage of a more accurate process monitoring, the main interest of this sensor deals with the control of the substrate concentration to a prespecified reference signal. Several experiments have been carried out first to validate the sensor, then to control the process evolution.     

Bioprocess monitoring by marker gene analysis

The optimization and the scale up of industrial fermentation processes require an efficient and possibly comprehensive analysis of the physiology of the production system throughout the process development. Furthermore, to ensure a good quality control of established bioprocesses, on-line analysis techniques for the determination of marker gene expression are of interest to monitor the productivity and the safety of bioprocesses. A prerequisite for such analyses is the knowledge of genes, the expression of which is critical either for the productivity or for the performance of the bioprocess. This work reviews marker genes that are specific indicators for stress- and nutrient-limitation conditions or for the physiological status of the bacterial production hosts Bacillus subtilis, Bacillus licheniformis and Escherichia coli. The suitability of existing gene expression analysis techniques for bioprocess monitoring is discussed. Analytical approaches that enable a robust and sensitive determination of selected marker mRNAs or proteins are presented.     

Integrated framework of nonlinear prediction and process monitoring for complex biological processes

Bioprocesses and biosystems have nonlinear and multiple operation patterns depending on the influent loads, temperatures, the activity of microorganisms, and other factors. In this paper, an integrated framework of nonlinear modeling and process monitoring methods is developed for a complex biological process. The proposed method is based on modeling by fuzzy partial least squares (FPLS) and on process monitoring by a statistical decomposition, which is suitable for predicting and supervising a nonlinear biological process. Case studies in the bio-simulated process and industrial biological plant show that the proposed method can give superior prediction and monitoring performance in complex biological plants compared to other linear and nonlinear methods, since it can effectively capture the nonlinear causal relationship within the biosystem. This gives us the integrated framework that is able to both model and monitor the nonlinear bioprocess simultaneously.     

Defined media and inert supports: their potential as solid-state fermentation production systems

Solid-state fermentation (SSF) using inert supports impregnated with chemically defined liquid media has several potential applications in both scientific studies and in the industrial production of high-value products, such as metabolites, biological control agents and enzymes. As a result of its more defined system, SSF on inert supports offers numerous advantages, such as improved process control and monitoring, and enhanced process consistency, compared with cultivation on natural solid substrates.     

At-line monitoring of a submerged filamentous bacterial cultivation using near-infrared spectroscopy

The use of near infra-red spectroscopy (NIRS) to monitor a submerged filamentous bacterial bioprocess was investigated. An industrial strain of the filamentous bacterium Streptomyces fradiae was cultured in a 12 litre stirred tank reactor (STR) using a complex medium. This mycelial 4 phase (oil, water, gas and solid) system produced highly complex and variable matrices, therefore monitoring such a complex fluid with NIRS represented a considerable challenge. Nevertheless, successful models for four key analytes (methyl oleate, glucose, glutamate and ammonium) were built at-line (rapid off-line) using NIRS. In the present study, the methods used to formulate, select and validate the models for the key analytes are discussed, with particular emphasis on how the model performance can be critically evaluated. Since previous reports on NIRS in monitoring bioprocesses have either involved simpler matrices, or, in filamentous systems, have not discussed how NIRS models can be critically assessed, the emphasis in the present study on providing an insight into the modelling process in such a complex matrix, may be particularly important to the applicability of NIRS to such industrial bioprocesses.     

A rapid monitoring assay for the detection of Salmonella spp. and Salmonella Senftenberg strain W775 in composts

AIMS: The composting process needs to be validated for its hygienic status in order to ensure that it is free of pathogens. Generally, this is evaluated through temperature monitoring, or additionally through active inoculation and monitoring of indicator organisms. We aimed to develop a monitoring method for the heat-resistant indicator organism Salmonella enterica ssp. enterica serovar Senftenberg strain W775 for detection in composting biowastes. METHODS AND RESULTS: The method development is comprised of: (i) optimization of molecular detection of bacteria belonging to the genus Salmonella; (ii) identification of a DNA marker for Salmonella strain W775; and (iii) development of a multiplex polymerase chain reaction (PCR)-based on both DNA markers. Subsequently, Salmonella strain W775 was inoculated and monitored during composting of biowastes in an industrial composting facility. CONCLUSIONS: A highly sensitive and specific detection of viable cells was obtained by enriching the compost sample prior to multiplex PCR analysis. Complete inactivation of Salmonella strain W775 was obtained within 4 days in an industrial composting facility at temperatures ranging between 41 and 57 degrees C. SIGNIFICANCE AND IMPACT OF THE STUDY: We describe a monitoring method for the simultaneous detection of naturally occurring Salmonella strains and artificially introduced Salmonella strain W775 in composting biowastes that can be applied in routine analysis.     

Hybrid-EKF: Hybrid model coupled with extended Kalman filter for real-time monitoring and control of mammalian cell culture

In a decade when Industry 4.0 and quality by design are major technology drivers of biopharma, automated and adaptive process monitoring and control are inevitable requirements and model-based solutions are key enablers in fulfilling these goals. Despite strong advancement in process digitalization, in most cases, the generated datasets are not sufficient for relying on purely data-driven methods, whereas the underlying complex bioprocesses are still not completely understood. In this regard, hybrid models are emerging as a timely pragmatic solution to synergistically combine available process data and mechanistic understanding. In this study, we show a novel application of the hybrid-EKF framework, that is, hybrid models coupled with an extended Kalman filter for real-time monitoring, control, and automated decision-making in mammalian cell culture processing. We show that, in the considered application, the predictive monitoring accuracy of such a framework improves by at least 35% when developed with hybrid models with respect to industrial benchmark tools based on PLS models. In addition, we also highlight the advantages of this approach in industrial applications related to conditional process feeding and process monitoring. With regard to the latter, for an industrial use case, we demonstrate that the application of hybrid-EKF as a soft sensor for titer shows a 50% improvement in prediction accuracy compared with state-of-the-art soft sensor tools.     

京津冀城市群区域产业协同的政策格局及评价

产业协同发展是京津冀区域协同发展的三个重点领域之一,科学合理的产业协同政策是加快实现这一发展目标的重要保障。通过对京津冀城市群区域产业协同政策事件的系统梳理,从区域、省际和城际3个尺度解读了产业协同政策的格局及其演进过程,并从新区域主义的管治视角进行了评价。研究认为:(1)京津冀产业协同发展进入了快速发展的机遇期,协同政策极大地推动了区域内跨地产业合作和城市间产业联系,有助于提高城市群整体竞争力;(2)不同空间尺度的产业协同政策关注的重点、发展的方向、演化的特征不同,当前城市间的产业协同政策与区域协同发展目标的关系不明确,产业协同对生态环境的改善尚不显著,亟需加强研究和统筹协调;(3)受城市行政区等级关系和竞争关系的影响,京津冀产业协同政策与市场调节无法实现高度契合统一,与新区域主义的管治理念并不相符,影响科学合理协同政策的制定与实施。研究对当前京津冀区域产业协同发展推进及其政策制定有重要的参考意义。     

Scale-down and parallel operation of the riboflavin production process with Bacillus subtilis

The establishment and the improvement of industrial bioprocesses calls for the selection of media compositions and process conditions in highly parallel experiments as well as for the intensified screening of new biocatalysts and improved production strains. This work presents for the first time the scale-down and the successful adaptation of an industrial riboflavin fed-batch production process with Bacillus subtilis to a fully automated setup with 48 parallel stirred bioreactors at a milliliter scale (10 mL). The feasibility of an intermittent feeding mode and a discontinuous at-line pH control for parallel cultivations over up to 53 h is demonstrated together with interlaced process analyses at a microliter scale for quasi-simultaneous at-line monitoring of biomass, substrate and product concentration. The discontinuous feeding mode necessitated an increased oxygen input, resulting in lower final biomass concentrations. However, the product yields and volumetric productivities in the milliliter setup were equivalent to the yields and productivities obtained during the reference cultivations at laboratory scale, which allows considering the automated system together with the developed schedule as a screening tool for high-throughput bioprocess design of the described production process.     

Software sensor design considering oscillating conditions as present in industrial scale fed‐batch cultivations

Investigations of inhomogeneous dynamics in industrial‐scale bioreactors can be realized in laboratory simulators. Such studies will be improved by on line observation of the growth of microorganisms and their product synthesis at oscillating substrate availability which represents the conditions in industrial‐scale fed‐batch cultivations. A method for the kinetic monitoring of such processes, supported by on line measurements accessible in industrial practice, is proposed. It consists of a software sensor (SS) system composed of a cascade structure. Process kinetics are simulated in models with a structure including time‐varying yield coefficients. SSs for measured variable kinetics have classical structures. The SS design of unmeasured variables is realized after a linear transformation using a logarithmic function. For these software sensors, a tuning procedure is proposed, at which an arbitrary choice of one tuning parameter value that guarantees stability of the monitoring system allows the calculation of the optimal values of six parameters. The effectiveness of the proposed monitoring approach is demonstrated with experimental data from a glucose‐limited fed‐batch process of Bacillus subtilis in a laboratory two‐compartment scale down reactor which tries to mimic the conditions present in industrial scale nutrient‐limited fed‐batch cultivations. Biotechnol. Bioeng. 2013; 110: 1945–1955. © 2013 Wiley Periodicals, Inc.     

Use of glucose consumption rate (GCR) as a tool to monitor and control animal cell production processes in packed-bed bioreactors

For animal cell cultures growing in packed-bed bioreactors where cell number cannot be determined directly, there is a clear need to use indirect methods that are not based on cell counts in order to monitor and control the process. One option is to use the glucose consumption rate (GCR) of the culture as an indirect measure to monitor the process in bioreactors. This study was done on a packed-bed bioreactor process using recombinant CHO cells cultured on Fibra-Cel disk carriers in perfusion mode at high cell densities. A key step in the process is the switch of the process from the cell growth phase to the production phase triggered by a reduction of the temperature. In this system, we have used a GCR value of 300 g of glucose per kilogram of disks per day as a criterion for the switch. This paper will present results obtained in routine operations for the monitoring and control of an industrial process at pilot-scale. The process operated with this GCR-based strategy yielded consistent, reproducible process performance across numerous bioreactor runs performed on multiple production sites.     

Indirect measurement of water content in an aseptic solid substrate cultivation pilot-scale bioreactor

A lack of models and sensors for describing and monitoring large-scale solid substrate cultivation (SSC) bioreactors has hampered industrial development and application of this type of process. This study presents an indirect dynamic measurement model for a 200-kg-capacity fixed-bed SSC bioreactor under periodic agitation. Growth of the filamentous fungus Gibberella fujikuroi on wheat bran was used as a case study. Real data were preprocessed using previously reported methodology. The model uses CO2 production rate and inlet air conditions to estimate average bed water content and average bed temperature. The model adequately reproduces the evolution of the average bed water content and can therefore be used as an on-line estimator in pilot-scale SSC bioreactors. To obtain a reasonable fit of the bed temperature, however, inlet air humidity measurements will have to be adjusted with a data reconciliation algorithm. Good estimation of temperature is important for the future design of improved water content estimation using state observers. The model also provides insight into understanding the complex behavior of the dynamic system, which could prove useful when establishing advanced model-based operational and control strategies.     

An automated system for biocide testing on biofilms*

The paper presents and discusses a novel on-line real-time non-destructive continuous-flow system for biocide testing on industrial biofilms. This laboratory system is capable of monitoring changes in growth, accumulation and respiratory activity of biofilms in response to biocidal treatment. The system incorporates a fouling monitor for continuous measuring of the rate of biofilm accumulation (heat transfer resistance), a sensor for monitoring of microbial activity (oxygen meter for monitoring the rate of biofilm respiratory activity), and subsystems necessary for microbial life support and control of operation parameters. Examples of system operation and testing of oxidizing and non-oxidizing biocides are presented. Received 25 May 1997/ Accepted in revised form 25 November 1997     

Biosensors: recent trends

One of the major bottlenecks in automation and process control of industrial bioprocesses is the lack of suitable sensing devices to accurately measure the concentrations of biomolecules. The measurement of ions (e.g., H⁺, NH₄⁺) and gases (e.g., O₂, CO₂, NH₃) using standard ion-selective and gas sensing electrodes respectively, is well established. Chemical analysis of biomolecules off-line is generally unreliable, labour intensive and may lead to contamination of the biological systems. Problems of maintaining sterile conditions are especially important when dealing with slow growing mammalian or plant cells in culture. Active research in the development of biosensors for monitoring fermentation processes, food production and pollution control, and for medical and veterinary applications is currently underway. This paper reviews recent approaches toward the development of biosensors which involve a biochemical interaction to measure the concentrations of biomolecules, primarily for the on-line monitoring and control of fermentation processes.     

蛋白质组学技术在工业发酵梭菌研究中的应用

介绍了目前应用较广泛的蛋白质组学技术的原理、应用及优缺点;总结了发酵工业中常用的梭菌属细菌;重点阐述了蛋白质组学技术在工业发酵梭状芽孢杆菌研究中的应用,为工业发酵菌种的改良和发酵工艺的优化提供理论依据。最后讨论了今后工业发酵菌种蛋白质组学研究的重点和方向。