Application of dielectric spectroscopy to unravel the physiological state of microorganisms: current state, prospects and limits

Flores-Cosío, G.; Herrera-López, Enrique J.; Arellano‐Plaza, Melchor; Gschaedler‐Mathis, Anne; Kirchmayr, Manuel R.; Amaya-Delgado, Lorena

doi:10.1007/s00253-020-10677-x

Cited by 24 publications

(19 citation statements)

References 94 publications

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“…Starting from the very beginning of the methanol consumption phase, within 1-2 h, XpermFiltr declined in all cultivations by about 10-20 g/L. This change in the culture dielectric properties under new conditions is a characteristic behavior as adaptation to another substrate and start of recombinant protein synthesis occurs [57]. The XpermFiltr behavior within the methanol consumption phase differed between Mut + and Mut S strains.…”

Section: In-situ Permittivity (Xpermfiltr) Based Biomass Estimatesmentioning

confidence: 89%

“…The reason for such XpermFiltr and DCW shifts in the comparably similar processes (like for the Dataset 3 experiments) can be caused by the varying permittivity of cell population caused by changes in the cell size and/or intracellular conductivity [57]. If one assumes that the intracellular conductivity remains unchanged for the morphologically different cell clusters, the varying dynamics of the cell population size could lead to differences between XpermFiltr and DCW.…”

Section: In-situ Permittivity (Xpermfiltr) Based Biomass Estimatesmentioning

confidence: 94%

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Application of In-Situ and Soft-Sensors for Estimation of Recombinant P. pastoris GS115 Biomass Concentration: A Case Analysis of HBcAg (Mut+) and HBsAg (MutS) Production Processes under Varying Conditions

Grīgs

Bolmanis

Galvanauskas

2021

Sensors

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Microbial biomass concentration is a key bioprocess parameter, estimated using various labor, operator and process cross-sensitive techniques, analyzed in a broad context and therefore the subject of correct interpretation. In this paper, the authors present the results of P. pastoris cell density estimation based on off-line (optical density, wet/dry cell weight concentration), in-situ (turbidity, permittivity), and soft-sensor (off-gas O2/CO2, alkali consumption) techniques. Cultivations were performed in a 5 L oxygen-enriched stirred tank bioreactor. The experimental plan determined varying aeration rates/levels, glycerol or methanol substrates, residual methanol levels, and temperature. In total, results from 13 up to 150 g (dry cell weight)/L cultivation runs were analyzed. Linear and exponential correlation models were identified for the turbidity sensor signal and dry cell weight concentration (DCW). Evaluated linear correlation between permittivity and DCW in the glycerol consumption phase (<60 g/L) and medium (for Mut+ strain) to significant (for MutS strain) linearity decline for methanol consumption phase. DCW and permittivity-based biomass estimates used for soft-sensor parameters identification. Dataset consisting from 4 Mut+ strain cultivation experiments used for estimation quality (expressed in NRMSE) comparison for turbidity-based (8%), permittivity-based (11%), O2 uptake-based (10%), CO2 production-based (13%), and alkali consumption-based (8%) biomass estimates. Additionally, the authors present a novel solution (algorithm) for uncommon in-situ turbidity and permittivity sensor signal shift (caused by the intensive stirrer rate change and antifoam agent addition) on-line identification and minimization. The sensor signal filtering method leads to about 5-fold and 2-fold minimized biomass estimate drifts for turbidity- and permittivity-based biomass estimates, respectively.

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Section: In-situ Permittivity (Xpermfiltr) Based Biomass Estimatesmentioning

confidence: 89%

Section: In-situ Permittivity (Xpermfiltr) Based Biomass Estimatesmentioning

confidence: 94%

Application of In-Situ and Soft-Sensors for Estimation of Recombinant P. pastoris GS115 Biomass Concentration: A Case Analysis of HBcAg (Mut+) and HBsAg (MutS) Production Processes under Varying Conditions

Grīgs

Bolmanis

Galvanauskas

2021

Sensors

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“…Усі ці методики однак є доволі складними і дорогими, тому наразі вони не отримали значного поширення. Натомість, однією з найбільш зручних, швидких і недорогих методик вивчення бактерій і біоклітин вважається імпедансна спектроскопія [10]. Ця техніка заснована на вимірюванні електрохімічного імпедансу (діелектричних спектрів) у широкому частотному інтервалі з їх подальшою інтерпретацією, що дозволяє отримати корисну інформацію про біологічні тканини чи бактеріальні суспензії.…”

Section: сучасна стоматологія 5/2020unclassified

Problems of identifying periodontopathogenic bacterial flora and potential solutions to them by mathematical modeling of an effective dielectric response using the example of S. aureus (reference strain)

Гончаренко¹,

Burgonskyi²,

Mykolaichuk³

2020

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The aim of the study was to create a multiparametric mathematical model describing the dielectric response of Staphylococcus aureus suspensions for its further use to interpret dielectric spectra and identify the parameters of periodontopathogenic bacterial flora, that would optimize diagnostic processes in periodontology. Materials and methods. The study was based on the use of the Bergman-Milton analytical spectral representation for the effective dielectric response, generalized to the case of inclusions (bacteria), which can be modeled as core-shell- spheroids. The developed software using the Matlab numerical computing environment allowed us to determine the effective dielectric conductivity and dielectric losses as a function of material and geometrical parameters of the bacterial suspension. The material parameters and the inclusion sizes (Staphylococcus aures – S. Aureus bacteria) were taken from literature sources; geometrical parameters characterizing the bacteria shape were considered as model variables. To illustrate the application of the method, the spectral density function of the simplest kind, sush as a homogeneous distribution of spheroidal shapes with a median corresponding to the spherical shape, was used. Results. The spectra of the real and imaginary part of the effective dielectric function εeff of S. Aureus aqueous suspensions in the frequency range of 1–104 KHz at different values of a nonsphericity parameter, characterizing the fluctuations of the bacterial shape around the spherical one, were calculated. It is shown that shape fluctuations can significantly affect Re εeff only at low frequencies, where they increase Re εeff. At high frequencies, the shape fluctuations only slightly reduce Re εeff. The imaginary part of the effective dielectric function (dielectric losses) shows a weak dependence on the nonsphericity parameter with in the entire frequency range. Other calculations indicate that the increase in the electrical conductivity of the plasma membrane, which characterizes S. Aureus dead bacteria, is accompanied by a marked decrease in Re εeff at frequencies below 1 MHz. Conclusion. By the example of S. Aureus, we demonstrated the use of a generalized spectral model of the effective dielectric response for the interpretation of the dielectric spectra of pathogenic microorganisms. The simplicity and analyticity of the model make it a convenient and promising tool for biophysical and medical studies. The generalized spectral model can be used to solve thel direct problem, namely to determine the influence of material and geometrical parameters of bacteria on their dielectric spectra, as well as to solve the inverse problem, which consists in finding the model parameters by processing the experimental dielectric spectra.

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“…Dielectric and electrokinetic properties of the cells can be strongly affected by changes of the structure of the cells [9] (see Figure 1). Dielectrophoresis (DEP) is a well-established technique that can be used to target these types of changes.…”

Section: Introductionmentioning

confidence: 99%

“…Structural changes of a cell are reflected in its dielectric and electrokinetic properties due to, e.g., changes in the conductivity of the membrane, the charge of membrane, and aggregation of protein. Schematics are based on descriptions of heat-induced changes in [9,15].…”

Section: Introductionmentioning

confidence: 99%

Cell Sorting Using Electrokinetic Deterministic Lateral Displacement

Beech

Tegenfeldt

2020

Micromachines

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We show that by combining deterministic lateral displacement (DLD) with electrokinetics, it is possible to sort cells based on differences in their membrane and/or internal structures. Using heat to deactivate cells, which change their viability and structure, we then demonstrate sorting of a mixture of viable and non-viable cells for two different cell types. For Escherichia coli, the size change due to deactivation is insufficient to allow size-based DLD separation. Our method instead leverages the considerable change in zeta potential to achieve separation at low frequency. Conversely, for Saccharomyces cerevisiae (Baker’s yeast) the heat treatment does not result in any significant change of zeta potential. Instead, we perform the sorting at higher frequency and utilize what we believe is a change in dielectrophoretic mobility for the separation. We expect our work to form a basis for the development of simple, low-cost, continuous label-free methods that can separate cells and bioparticles based on their intrinsic properties.

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Application of dielectric spectroscopy to unravel the physiological state of microorganisms: current state, prospects and limits

Cited by 24 publications

References 94 publications

Application of In-Situ and Soft-Sensors for Estimation of Recombinant P. pastoris GS115 Biomass Concentration: A Case Analysis of HBcAg (Mut+) and HBsAg (MutS) Production Processes under Varying Conditions

Application of In-Situ and Soft-Sensors for Estimation of Recombinant P. pastoris GS115 Biomass Concentration: A Case Analysis of HBcAg (Mut+) and HBsAg (MutS) Production Processes under Varying Conditions

Problems of identifying periodontopathogenic bacterial flora and potential solutions to them by mathematical modeling of an effective dielectric response using the example of S. aureus (reference strain)

Cell Sorting Using Electrokinetic Deterministic Lateral Displacement

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