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Fluorescence spectroscopy and chemometric modeling for bioprocess monitoring.

Faassen SM, Hitzmann B - Sensors (Basel) (2015)

Bottom Line: During a cultivation process significant changes occur in the fluorescence spectra.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.Beyond that, the PLS-method is the most frequently used chemometric method for the calculation of process models and prediction of process variables.

View Article: PubMed Central - PubMed

Affiliation: Process Analytics and Cereal Science, Institute of Food Science and Biotechnology, University Hohenheim, Garbenstraße 23, 70599 Stuttgart, Germany. Saskia.faassen@uni-hohenheim.de.

ABSTRACT
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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Related in: MedlinePlus

Contour plot of an excitation-emission matrix measured with the BioView® sensor from S. cerevisiae cultivation with fluorescence maxima of flavin (1); riboflavin (2); NADH (3); NADPH (4); pyrodoxin (5); tryptophan (6) and tyrosine (7).
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sensors-15-10271-f002: Contour plot of an excitation-emission matrix measured with the BioView® sensor from S. cerevisiae cultivation with fluorescence maxima of flavin (1); riboflavin (2); NADH (3); NADPH (4); pyrodoxin (5); tryptophan (6) and tyrosine (7).

Mentions: A light quantum of energy hvA supplied by an external source is absorbed by the fluorophore, creating an excited electronic singlet state (S1 or S2). On these energy levels the fluorophores can exist in different vibrational energy levels (v) corresponding to the Franck-Condon-principle. From the higher vibrational level of S1 or S2 the fluorophore is rapidly relaxing to the lowest vibrational level due to internal conversion. A photon with energy hvF is emitted when the fluorophore is returning to its electronic ground state S0. The energy of this emission photon is lower, and therefore of a longer wavelength than the excitation photon. This behavior can be seen in Figure 2, where in the upper left triangle of the spectrum no fluorescence signal can be seen. This so-called Stoke’s shift enables the high sensitivity of the fluorescence technique because it allows the detection of emission photons against a low background, isolated from excitation photons [62]. Characteristic features of fluorophores are the quantum yield and the lifetime. The ratio of the number of excited and emitted photons is the quantum yield, and the lifetime is defined by the average time the molecule spends in the excited state before it returns to its ground state [63]. However, the fluorescence yield can be influenced by different effects which involve energy transfer and absorption. For example, the so-called inner filter effects reduce the intensity of the fluorescence measurements when non-fluorescent components of the medium absorb excitation or emission radiation while reducing the fluorescence yield of an observed fluorophore [64]. The excited state fluorescence lifetime also changes with changes in the environment. Furthermore, the culture fluorescence depends on bioprocess variables, such as the optical density (OD), viscosity, pH, the aeration of the bioreactor and a lot of further the fluorescence measurements affecting variables [22].


Fluorescence spectroscopy and chemometric modeling for bioprocess monitoring.

Faassen SM, Hitzmann B - Sensors (Basel) (2015)

Contour plot of an excitation-emission matrix measured with the BioView® sensor from S. cerevisiae cultivation with fluorescence maxima of flavin (1); riboflavin (2); NADH (3); NADPH (4); pyrodoxin (5); tryptophan (6) and tyrosine (7).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4481931&req=5

sensors-15-10271-f002: Contour plot of an excitation-emission matrix measured with the BioView® sensor from S. cerevisiae cultivation with fluorescence maxima of flavin (1); riboflavin (2); NADH (3); NADPH (4); pyrodoxin (5); tryptophan (6) and tyrosine (7).
Mentions: A light quantum of energy hvA supplied by an external source is absorbed by the fluorophore, creating an excited electronic singlet state (S1 or S2). On these energy levels the fluorophores can exist in different vibrational energy levels (v) corresponding to the Franck-Condon-principle. From the higher vibrational level of S1 or S2 the fluorophore is rapidly relaxing to the lowest vibrational level due to internal conversion. A photon with energy hvF is emitted when the fluorophore is returning to its electronic ground state S0. The energy of this emission photon is lower, and therefore of a longer wavelength than the excitation photon. This behavior can be seen in Figure 2, where in the upper left triangle of the spectrum no fluorescence signal can be seen. This so-called Stoke’s shift enables the high sensitivity of the fluorescence technique because it allows the detection of emission photons against a low background, isolated from excitation photons [62]. Characteristic features of fluorophores are the quantum yield and the lifetime. The ratio of the number of excited and emitted photons is the quantum yield, and the lifetime is defined by the average time the molecule spends in the excited state before it returns to its ground state [63]. However, the fluorescence yield can be influenced by different effects which involve energy transfer and absorption. For example, the so-called inner filter effects reduce the intensity of the fluorescence measurements when non-fluorescent components of the medium absorb excitation or emission radiation while reducing the fluorescence yield of an observed fluorophore [64]. The excited state fluorescence lifetime also changes with changes in the environment. Furthermore, the culture fluorescence depends on bioprocess variables, such as the optical density (OD), viscosity, pH, the aeration of the bioreactor and a lot of further the fluorescence measurements affecting variables [22].

Bottom Line: During a cultivation process significant changes occur in the fluorescence spectra.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.Beyond that, the PLS-method is the most frequently used chemometric method for the calculation of process models and prediction of process variables.

View Article: PubMed Central - PubMed

Affiliation: Process Analytics and Cereal Science, Institute of Food Science and Biotechnology, University Hohenheim, Garbenstraße 23, 70599 Stuttgart, Germany. Saskia.faassen@uni-hohenheim.de.

ABSTRACT
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.

Show MeSH
Related in: MedlinePlus