Dielectric measurement of cell death

Patel, Pareshkumar; Markx, Gerard H.

doi:10.1016/j.enzmictec.2008.09.005

Cited by 116 publications

(95 citation statements)

References 100 publications

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“…It was probably a result of a combination of a decreasing cell diameter (Figures 4 and 7) and an increase in membrane conductance during death phase. 38 The The overall qualitative pattern of all b-dispersion parameters was similar for both cultivations. In phase B II of the pilot scale cultivation, De max gave higher values relative to De Fogale when compared with the lab scale cultivation.…”

Section: Multifrequency Permittivity Measurements and Analysis Of Calmentioning

confidence: 74%

“…5,[64][65][66][67][68] In late stages of cultures, changes in cell diameter and viability typically occur, leading to changes in several parameters (C M , r i , and others). 20,29,38 An easily comprehensible example for the complexity of the analysis is that according to our results, an increase in f C might occur either as a result of a decrease in cell size (Eq. 2), viability (beginning of death phase), or as an indicator of a metabolic shift of the culture (phase B II in lab scale).…”

Section: Multifrequency Permittivity Measurements and Analysis Of Calmentioning

confidence: 80%

“…The equation for f C changes for situations of low cellular viability or high membrane conductivity. 37,38 In this study, this relationship could be neglected for the most important part of our results because viability remained high when important changes in f C occurred.…”

Section: Theoretical Backgroundmentioning

confidence: 96%

“…C M is generally interpreted as a measure of the ''wrinkliness,'' that is, the level of folding of the cellular membrane. 38 Whereas originally reported to be a biological constant with a value of 1 AE 0.5 lF/cm. 2,7,37 C M was in more recent studies found to be depending on viability and physiological state.…”

Section: Multifrequency Permittivity Measurements and Analysis Of Calmentioning

confidence: 99%

“…22,24 It also changes after viral infection and increases significantly after overexpression of cation channels, 30,49 being particularly affected by processes directly concerning cellular membrane properties, for example, exocytosis (loss of microvilli), viral release, and apoptosis. 20,29,38 One study reports that changes in C M might, in combination with a rather small drop in cell size, be responsible for changes in permittivity. These authors attributed difference in permittivity to unknown changes in membrane structure (and therefore in C M ) and found an excellent correlation between the permittivity signal and physiological state during perfusion cultures of hybridoma cells.…”

Section: Multifrequency Permittivity Measurements and Analysis Of Calmentioning

confidence: 99%

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Multifrequency permittivity measurements enable on‐line monitoring of changes in intracellular conductivity due to nutrient limitations during batch cultivations of CHO cells

Ansorge

Esteban

Schmid

2009

Biotechnology Progress

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Lab and pilot scale batch cultivations of a CHO K1/dhfr À host cell line were conducted to evaluate on-line multifrequency permittivity measurements as a process monitoring tool. The b-dispersion parameters such as the characteristic frequency (f C ) and the permittivity increment (De max ) were calculated on-line from the permittivity spectra. The dual-frequency permittivity signal correlated well with the off-line measured biovolume and the viable cell density. A significant drop in permittivity was monitored at the transition from exponential growth to a phase with reduced growth rate. Although not reflected in off-line biovolume measurements, this decrease coincided with a drop in OUR and was probably caused by the depletion of glutamine and a metabolic shift occurring at the same time. Sudden changes in cell density, cell size, viability, capacitance per membrane area (C M ), and effects caused by medium conductivity (r m ) could be excluded as reasons for the decrease in permittivity. After analysis of the process data, a drop in f C as a result of a fall in intracellular conductivity (r i ) was identified as responsible for the observed changes in the dual-frequency permittivity signal. It is hypothesized that the b-dispersion parameter f C is indicative of changes in nutrient availability that have an impact on intracellular conductivity r i . On-line permittivity measurements consequently not only reflect the biovolume but also the physiological state of mammalian cell cultures. These findings should pave the way for a better understanding of the intracellular state of cells and render permittivity measurements an important tool in process development and control.

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Section: Multifrequency Permittivity Measurements and Analysis Of Calmentioning

confidence: 74%

Section: Multifrequency Permittivity Measurements and Analysis Of Calmentioning

confidence: 80%

Section: Theoretical Backgroundmentioning

confidence: 96%

Section: Multifrequency Permittivity Measurements and Analysis Of Calmentioning

confidence: 99%

Section: Multifrequency Permittivity Measurements and Analysis Of Calmentioning

confidence: 99%

See 3 more Smart Citations

Multifrequency permittivity measurements enable on‐line monitoring of changes in intracellular conductivity due to nutrient limitations during batch cultivations of CHO cells

Ansorge

Esteban

Schmid

2009

Biotechnology Progress

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Dielectrophoretic Studies of Bioparticles

2017

Dielectrophoresis

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Capacitance spectroscopy enables real‐time monitoring of early cell death in mammalian cell culture

Ketcham²,

Corredor

et al. 2022

Biotechnology Journal

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Background/Aims Previous work developed a quantitative model using capacitance spectroscopy in an at‐line setup to predict the dying cell percentage measured from a flow cytometer. This work aimed to transfer the at‐line model to monitor lab‐scale bioreactors in real‐time, waiving the need for frequent sampling and enabling precise controls. Methods and Results Due to the difference between the at‐line and in‐line capacitance probes, direct application of the at‐line model resulted in poor accuracy and high prediction bias. A new model with a variable range and offering similar spectral shape across all probes was first constructed, improving prediction accuracy. Moreover, the global calibration method included the variance of different probes and scales in the model, reducing prediction bias. External parameter orthogonalization, a preprocessing method, also mitigated the interference from feeding, which further improved model performance. The root‐mean‐square error of prediction of the final model was 6.56% (8.42% of the prediction range) with an R2 of 92.4%. Conclusion The culture evolution trajectory predicted by the in‐line model captured the cell death and alarmed cell death onset earlier than the trypan blue exclusion test. Additionally, the incorporation of at‐line spectra following orthogonal design into the calibration set was shown to generate calibration models that are more robust than the calibration models constructed using the in‐line spectra only. This is advantageous, as at‐line spectral collection is easier, faster, and more material‐sparing than in‐line spectra collection.

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Dielectric measurement of cell death

Cited by 116 publications

References 100 publications

Multifrequency permittivity measurements enable on‐line monitoring of changes in intracellular conductivity due to nutrient limitations during batch cultivations of CHO cells

Multifrequency permittivity measurements enable on‐line monitoring of changes in intracellular conductivity due to nutrient limitations during batch cultivations of CHO cells

Dielectrophoretic Studies of Bioparticles

Capacitance spectroscopy enables real‐time monitoring of early cell death in mammalian cell culture

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