Biomedical subjects

Carl-Fredrik Mandenius

Publications and source records attributed to Carl-Fredrik Mandenius.

8 recordsLinked to original sources

PubMed2004

Off-line monitoring of bacterial stress response during recombinant protein production using an optical biosensor.

A surface plasmon resonance (SPR) biosensor was used to monitor the profiles of the heat-shock protein (DnaK) and the expression of a heterologous protein to map the dynamics of the cellular stress response in Escherichia coli. As expression system was used an E. coli strain overproducing human recombinant superoxide dismutase (rhSOD). Expression of DnaK showed complex patterns differing with strength of induction. The strong up-regulation of DnaK expression was observed in all cultivations which over-produced of rhSOD. Similar patterns were not observed in non-induced reference cultures. Differences in DnaK concentration profiles were correlated with induction strength. Presented data, carried out in shake flask and glucose limited fed-batch cultivation, show a good consistency with previously published transcriptional profiling results and provide complementary information to understand stress response related to overproduction of recombinant protein. The study also demonstrates the feasibility of using the SPR as a two channel protein array for monitoring of intracellular components.

Bioreactors↗

PubMed2004

On-line multisensor monitoring of yogurt and filmjölk fermentations on production scale.

Near-infrared (NIR) spectrometry and electronic nose (EN) data were used for on-line monitoring of yogurt and filmjölk (a Swedish yogurt-like sour milk) fermentations under industrial conditions. The NIR and EN signals were selected by evaluation of principal component analysis loading vectors and further analyzed by studying the variability of the selected principal components. First principal components for the NIR and the EN signals were used for on-line generation of a process trajectory plot visualizing the actual state of fermentation. The NIR signals were also used to set up empirical partial least-squares (PLS) models for prediction of the cultures' pH and titratable acidity (expressed as Thorner degrees, degrees T). By using five or six PLS factors the models yielded acceptable predictions that could be further improved by increasing the number of reliable and precise calibration data. The presented results demonstrate that the fusion of the NIR and EN signals has a potential for rapid on-line monitoring and assessment of process quality of yogurt fermentation.

Cultured Milk Products↗

PubMed2004

Evaluation of disruption methods for the release of intracellular recombinant protein from Escherichia coli for analytical purposes.

The aim of the present study was to find disruption methods that allow fast and reproducible measurement of intracellular recombinant proteins with potential for on-line application. Production of rhSOD (recombinant human superoxide dismutase) by Escherichia coli was used as a model. Three methods of cell disruption, sonication, osmotic shock and chemical treatment using a non-ionic surfactant, were critically compared with respect to efficiency and reproducibility of the release of rhSOD. The release of the recombinant protein was monitored by (i) measurement of the protein content in cell-culture extracts using an SPR (surface plasmon resonance) biosensor, and (ii) assaying the enzyme activity with a colorimetric reagent using a spectrophotometer. Disruption by the non-ionic surfactant showed the best performance in terms of simplicity, reproducibility and efficiency of sample treatment. The surfactant did not interfere with the rhSOD binding to the antibody immobilized on the SPR chip or with the rhSOD activity assay. When comparing the two detection methods during monitoring of an E. coli cultivation, comparable results were obtained.

Bacteriolysis↗

PubMed2003

Bioprocess control from a multivariate process trajectory.

A multivariate bioprocess control approach, capable of tracking a pre-set process trajectory correlated to the biomass or product concentration in the bioprocess is described. The trajectory was either a latent variable derived from multivariate statistical process monitoring (MSPC) based on partial least squares (PLS) modeling, or the absolute value of the process variable. In the control algorithm the substrate feed pump rate was calculated from on-line analyzer data. The only parameters needed were the substrate feed concentration and the substrate yield of the growth-limiting substrate. On-line near-infrared spectroscopy data were used to demonstrate the performance of the control algorithm on an Escherichia coli fed-batch cultivation for tryptophan production. The controller showed good ability to track a defined biomass trajectory during varying process dynamics. The robustness of the control was high, despite significant external disturbances on the cultivation and control parameters.

Algorithms↗

PubMed2003

Integration of distributed multi-analyzer monitoring and control in bioprocessing based on a real-time expert system.

A computer system solution for integration of a distributed bioreactor monitoring and control instrumentation on the laboratory scale is described. Bioreactors equipped with on-line analyzers for mass spectrometry, near-infrared spectroscopy, electrochemical probes and multi-array gas sensors and their respective software were networked through a real-time expert systems platform. The system allowed data transmission of more than 1800 different signals from the instrumentation, including signals from gas sensors, electrodes, spectrometer detectors, balances, flowmeters, etc., and were used for processing and carrying out a number of computational tasks such as partial least-square regression, principal component analysis, artificial neural network modelling, heuristic decision-making and adaptive control. The system was demonstrated on different cultivations/fermentations which illustrated sensor fusion control, multivariate statistical process monitoring, adaptive glucose control and adaptive multivariate control. The performance of these examples showed high operational stability and reliable function and meet typical requirements for production safety and quality.

Algorithms↗

PubMed2002

Sensor fusion for on-line monitoring of yoghurt fermentation.

Measurement data from an electronic nose (EN), a near-infrared spectrometer (NIRS) and standard bioreactor probes were used to follow the course of lab-scale yoghurt fermentation. The sensor signals were fused using a cascade neural network: a primary network predicted quantitative process variables, including lactose, galactose and lactate; a secondary network predicted a qualitative process state variable describing critical process phases, such as the onset of coagulation or the harvest time. Although the accuracy of the neural network prediction was acceptable and comparable with the off-line reference assay, its stability and performance were significantly improved by correction of faulty data. The results demonstrate that on-line sensor fusion with the chosen analyzers improves monitoring and quality control of yoghurt fermentation with implications to other fermentation processes.

Animals↗

PubMedDate not supplied

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.

Artificial Organs↗

PubMedDate not supplied

Growth behavior in plant cell cultures based on emissions detected by a multisensor array.

The use of a multisensor array based on chemical gas sensors to monitor plant cell cultures is described. The multisensor array, also referred to as an electronic nose, consisted of 19 different metal oxide semiconductor sensors and one carbon dioxide sensor. The device was used to continuously monitor the off-gas from two plant cell suspension cultures, Morinda citrifolia and Nicotiana tabacum, cultivated under batch conditions. By analyzing the multiarray responses using two pattern recognition methods, principal component analysis and artificial neural networks, it was possible to monitor the course of the cultivations and, in turn, to predict (1) the biomass concentration in both systems and (2) the formation of the secondary metabolite, antraquinone, by M. citrifolia. The results identify the multisensor array method as a potentially useful analytical tool for monitoring plant process variables that are otherwise difficult to analyze on-line.

Biosensing Techniques↗