Recent developments in the monitoring,modeling and control of biological production systems

Current trends in the development of methods for monitoring, modeling and controlling biological production systems are reviewed from a bioengineering perspective. The ability to measure intracellular conditions in bioprocesses using genomics and other bioinformatics tools is addressed. Devices provided via micromachining techniques and new real-time optical technology are other novel methods that may facilitate biosystem engineering. Mathematical modeling of data obtained from bioinformatics or real-time monitoring methods are necessary in order to handle the dense flows of data that are generated. Furthermore, control methods must be able to cope with these data flows in efficient ways that can be implemented in plant-wide computer communication systems.Mini-review for the proceedings of the M3C conference     

Reciprocal bidirectional plasticity of parallel fiber receptive fields in cerebellar Purkinje cells and their afferent interneurons

The highly specific relationships between parallel fiber (PF) and climbing fiber (CF) receptive fields in Purkinje cells and interneurons suggest that normal PF receptive fields are established by CF-specific plasticity. To test this idea, we used PF stimulation that was either paired or unpaired with CF activity. Conspicuously, unpaired PF stimulation that induced long-lasting, very large increases in the receptive field sizes of Purkinje cells induced long-lasting decreases in receptive field sizes of their afferent interneurons. In contrast, PF stimulation paired with CF activity that induced long-lasting decreases in the receptive fields of Purkinje cells induced long-lasting, large increases in the receptive fields of interneurons. These properties, and the fact the mossy fiber receptive fields were unchanged, suggest that the receptive field changes were due to bidirectional PF synaptic plasticity in Purkinje cells and interneurons.     

Assessment of the performance of a fed-batch cultivation from the preculture quality using an electronic nose

An electronic nose, a gas-phase multisensor system, was used to monitor precultivations of a recombinant tryptophan-producing Escherichia coli strain. The electronic nose signals showed a high correlation toward the main stages of the precultivations, namely, exponential growth, oxygen-limited growth, and glucose depletion. Principal component analysis (PCA) of the electronic nose signals was performed and shown to be useful for monitoring preculture progression. More importantly, PCA also allowed a qualitative assessment of the preculture performance during subsequent fed-batch cultivations. The electronic nose signals from the precultures showed, furthermore, a high correlation to the time of phosphate limitation and the tryptophan yield coefficient of the subsequent fed-batch cultivations, which allowed an accurate prediction of these process variables using partial least squares (PLS). The results demonstrate on data from 12 cultivations how the electronic nose can be a useful tool for the assessment of inoculum quality, thereby providing means of reducing batch-to-batch variation and increasing the productivity of bioprocesses.     

Analysis of carbohydrates using liquid chromatography--surface plasmon resonance immunosensing systems

An immunosensing system based on surface plasmon resonance (SPR) was used for on-line detection and characterization of carbohydrate molecules separated by high-performance liquid chromatography. These analytes, with or without serum, were continuously separated and analyzed in the combined liquid chromatography-surface plasmon resonance (LC-SPR) system. By using weak and readily reversible monoclonal antibodies, the SPR system allowed specific on-line monitoring of the substances. To increase the specificity of the immunosensor, nonrelevant antibodies were used as reference in a serial flow cell. The sensitivity of the LC-SPR system was dependent on molecular weight of the carbohydrate, affinity of binding, and design of the sensor.     

Intracellular monitoring of superoxide dismutase expression in an Escherichia coli fed-batch cultivation using on-line disruption with at-line surface plasmon resonance detection

An on-line cell disruption system for at-line monitoring of the intracellular concentration of recombinant human superoxide dismutase (rhSOD) in a genetically modified Escherichia coli strain, HMS174(DE3) (pET11a/rhSOD), in bioreactor cultivations is described. The sampled bacteria were disrupted on-line by rapid mixing with a nonionic detergent. The recombinant protein content of the lysed bacterial sample was quantitated by a subsequent surface plasmon resonance biosensor with a specific monoclonal antibody. Extraction efficiency of the monitoring system was optimized with respect to the flow rate ratio of the cell suspension and the detergent at relevant cell densities with the aim to attain rapid monitoring. Monitoring was demonstrated for a shake flask culture and a glucose-limited fed-batch cultivation. The results are compared with a traditional enzyme-linked immunosorbent assay method showing a correlation coefficient of R2 = 0.97. Extraction efficiency of rhSOD reached 95-99% at a total processing time of 1.8-2.6 min and a contact time of 0.8-1.4 min. The possibility of extending the monitoring system to other intracellular proteins is discussed.     

Soft sensors in bioprocessing: a status report and recommendations

The following report with recommendations is the result of an expert panel meeting on soft sensor applications in bioprocess engineering that was organized by the Measurement, Monitoring, Modelling and Control (M3C) Working Group of the European Federation of Biotechnology - Section of Biochemical Engineering Science (ESBES). The aim of the panel was to provide an update on the present status of the subject and to identify critical needs and issues for the furthering of the successful development of soft sensor methods in bioprocess engineering research and for industrial applications, in particular with focus on biopharmaceutical applications. It concludes with a set of recommendations, which highlight current prospects for the extended use of soft sensors and those areas requiring development.     

Engineering design methodology for bio-mechatronic products

Four complex biotechnology products/product systems (a protein purification system, a bioreactor system, a surface plasmon resonance biosensor, and an enzymatic glucose analyzer) are analyzed using conceptual design principles. A design model well-known in mechanical system design, the Hubka-Eder (HE) model, is adapted to biotechnology products that exemplify combined technical systems of mechanical, electronic, and biological components, here referred to as bio-mechatronic systems. The analysis concludes that an extension of the previous HE model with a separate biological systems entity significantly contributes to facilitating the functional and systematic analyses of bio-mechatronic systems.     

Sensor fusion with on-line gas emission multisensor arrays and standard process measuring devices in baker's yeast manufacturing process

The use of a multisensor array for measuring the emission from a production-scale baker's yeast manufacturing process is reported. The sensor array, containing 14 different gas-sensitive semiconductor devices and an infrared gas sensor, was used to monitor the gas emission from a yeast culture bioreactor during fed-batch operation. The signal pattern from the sensors was evaluated in relation to two key process variables, the cell mass and the ethanol concentrations. Fusion with the on-line sensor signals for reactor weight and aeration rate made it possible to estimate cell mass and ethanol concentration using computation with backpropagating artificial neural nets. Identification of process states with the same fusion of sensor signals was realized using principal component analysis. (c) 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 55: 427-438, 1997.     

Toward preclinical predictive drug testing for metabolism and hepatotoxicity by using in vitro models derived from human embryonic stem cells and human cell lines - a report on the Vitrocellomics EU-project

Drug-induced liver injury is a common reason for drug attrition in late clinical phases, and even for post-launch withdrawals. As a consequence, there is a broad consensus in the pharmaceutical industry, and within regulatory authorities, that a significant improvement of the current in vitro test methodologies for accurate assessment and prediction of such adverse effects is needed. For this purpose, appropriate in vivo-like hepatic in vitro models are necessary, in addition to novel sources of human hepatocytes. In this report, we describe recent and ongoing research toward the use of human embryonic stem cell (hESC)-derived hepatic cells, in conjunction with new and improved test methods, for evaluating drug metabolism and hepatotoxicity. Recent progress on the directed differentiation of human embryonic stem cells to the functional hepatic phenotype is reported, as well as the development and adaptation of bioreactors and toxicity assay technologies for the testing of hepatic cells. The aim of achieving a testing platform for metabolism and hepatotoxicity assessment, based on hESC-derived hepatic cells, has advanced markedly in the last 2-3 years. However, great challenges still remain, before such new test systems could be routinely used by the industry. In particular, we give an overview of results from the Vitrocellomics project (EU Framework 6) and discuss these in relation to the current state-of-the-art and the remaining difficulties, with suggestions on how to proceed before such in vitro systems can be implemented in industrial discovery and development settings and in regulatory acceptance.     

Electronic nose for estimation of product concentration in mammalian cell cultivation

The off-gas composition from perfusion cultivation of a CHO-cell line producing recombinant human blood coagulation Factor VIII is monitored with an electronic nose. It is shown that the electronic nose in combination with an artificial neural network can be used for on-line estimation of the Factor VIII concentration in production-scale cultivations. The obtained prediction error (1†) for the Factor VIII concentration was 1.1 IU/ml. The potential of the electronic nose for estimation of viable cell count is outlined in laboratory-scale Factor VIII cultivations. The obtained prediction error (1†) for the viable cell count was 0.4᎒⁶ cells/ml. The results show that this non-invasive method is potentially useful for on-line bioprocess monitoring.