Use of Bioanalytical Systems for the Improvement of Industrial Tryptophan Production

Ulber, Roland; Protsch, Carsten; Solle, Dörte; Hitzmann, Bernd; Willke, Birgit; Faurie, Robert; Scheper, Thomas

doi:10.1002/1618-2863(200107)1:1<15::aid-elsc15>3.0.co;2-1

Cited by 8 publications

(8 citation statements)

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“…It can be combined with chemometric evaluation techniques for chemometric modelling, [41]. Ulber et al have described a 10,000 l indol and serine to tryptophane biotransformation monitored by 2D fluorimetry, and managed to increase the yields up to 20% thus reducing significantly downstream costs and pollution [42]. Wolf et al used neural networks for non-linear analysis of the complex 2D absorbance/emission spectra for on-line monitoring of biofilm culture in a bioremediation process [43].…”

Section: Fluorescencesupporting

confidence: 39%

Real-time bioprocess monitoring

Vojinović¹,

Cabral²,

Fonseca³

2006

Sensors and Actuators B: Chemical

191

100

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Section: Fluorescencesupporting

confidence: 39%

Real-time bioprocess monitoring

Vojinović¹,

Cabral²,

Fonseca³

2006

Sensors and Actuators B: Chemical

191

100

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“…Multi-analyte monitoring of complex industrial bioprocesses [16,17] Wide range of process information accessible Weak scattering of cell culture broths SSRS (shifted subtracted Raman spectroscopy) [19] High speed and sensitivity…”

Section: Resultssupporting

confidence: 39%

“…Raman spectroscopy is based on the phenomena of shifted wavelength scattering of molecules excited with monochromatic light due to inelastic collisions of photons with the molecule. It is suitable for multi-analyte monitoring of complex industrial bioprocesses on-line [16,17] as well as to perform differentiated measurements of certain parameters, for example, the attempt of Shaw et al [18] to measure the glucose-ethanol biotransformation by yeast with Raman spectroscopy. The applied FT-Raman spectroscopy gave data for PLS and led to predictions with a correlation coefficient R 2 >0.9 for glucose and ethanol.…”

Section: Raman Spectroscopymentioning

confidence: 47%

Optical sensor systems for bioprocess monitoring

2003

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Bioreactors are closed systems in which microorganisms can be cultivated under defined, controllable conditions that can be optimized with regard to viability, reproducibility, and product-oriented productivity. To drive the biochemical reaction network of the biological system through the desired reaction optimally, the complex interactions of the overall system must be understood and controlled. Optical sensors which encompass all analytical methods based on interactions of light with matter are efficient tools to obtain this information. Optical sensors generally offer the advantages of noninvasive, nondestructive, continuous, and simultaneous multianalyte monitoring. However, at this time, no general optical detection system has been developed. Since modern bioprocesses are extremely complex and differ from process to process (e.g., fungal antibiotic production versus mammalian cell cultivation), appropriate analytical systems must be set up from different basic modules, designed to meet the special demands of each particular process. In this minireview, some new applications in bioprocess monitoring of the following optical sensing principles will be discussed: UV spectroscopy, IR spectroscopy, Raman spectroscopy, fluorescence spectroscopy, pulsed terahertz spectroscopy (PTS), optical biosensors, in situ microscope, surface plasmon resonance (SPR), and reflectometric interference spectroscopy (RIF).

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“…The principle of this measurement method is the interaction of light and matter. For this reason, a fast and non-invasive measurement technique is used as a requirement for on-line and real-time supervision and control for bioprocesses [ 61 ].…”

Section: Fluorescence Spectroscopymentioning

confidence: 99%

Fluorescence Spectroscopy and Chemometric Modeling for Bioprocess Monitoring

Faassen

Hitzmann

2015

Sensors

106

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On-line sensors for the detection of crucial process parameters are desirable for the monitoring, control and automation of processes in the biotechnology, food and pharma industry. Fluorescence spectroscopy as a highly developed and non-invasive technique that enables the on-line measurements of substrate and product concentrations or the identification of characteristic process states. During a cultivation process significant changes occur in the fluorescence spectra. By means of chemometric modeling, prediction models can be calculated and applied for process supervision and control to provide increased quality and the productivity of bioprocesses. A range of applications for different microorganisms and analytes has been proposed during the last years. This contribution provides an overview of different analysis methods for the measured fluorescence spectra and the model-building chemometric methods used for various microbial cultivations. Most of these processes are observed using the BioView® Sensor, thanks to its robustness and insensitivity to adverse process conditions. Beyond that, the PLS-method is the most frequently used chemometric method for the calculation of process models and prediction of process variables.

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Use of Bioanalytical Systems for the Improvement of Industrial Tryptophan Production

Cited by 8 publications

References 0 publications

Real-time bioprocess monitoring

Real-time bioprocess monitoring

Optical sensor systems for bioprocess monitoring

Fluorescence Spectroscopy and Chemometric Modeling for Bioprocess Monitoring

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