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Dielectrophoretic characterization of peroxidized retinal pigment epithelial cells as a model of age-related macular degeneration

BMC Ophthalmology volume 24, Article number: 340 (2024) Cite this article

Abstract

Background

Age-related macular degeneration (AMD) is a prevalent ocular pathology affecting mostly the elderly population. AMD is characterized by a progressive retinal pigment epithelial (RPE) cell degeneration, mainly caused by an impaired antioxidative defense. One of the AMD therapeutic procedures involves injecting healthy RPE cells into the subretinal space, necessitating pure, healthy RPE cell suspensions. This study aims to electrically characterize RPE cells to demonstrate a possibility using simulations to separate healthy RPE cells from a mixture of healthy/oxidized cells by dielectrophoresis.

Methods

BPEI-1 rat RPE cells were exposed to hydrogen peroxide to create an in-vitro AMD cellular model. Cell viability was evaluated using various methods, including microscopic imaging, impedance-based real-time cell analysis, and the MTS assay. Healthy and oxidized cells were characterized by recording their dielectrophoretic spectra, and electric cell parameters (crossover frequency, membrane conductivity and permittivity, and cytoplasm conductivity) were computed. A COMSOL simulation was performed on a theoretical microfluidic-based dielectrophoretic separation chip using these parameters.

Results

Increasing the hydrogen peroxide concentration shifted the first crossover frequency toward lower values, and the cell membrane permittivity progressively increased. These changes were attributed to progressive membrane peroxidation, as they were diminished when measured on cells treated with the antioxidant N-acetylcysteine. The changes in the crossover frequency were sufficient for the efficient separation of healthy cells, as demonstrated by simulations.

Conclusions

The study demonstrates that dielectrophoresis can be used to separate healthy RPE cells from oxidized ones based on their electrical properties. This method could be a viable approach for obtaining pure, healthy RPE cell suspensions for AMD therapeutic procedures.

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Background

In the field of regenerative medicine, retinal pigment epithelial (RPE) transplantation as cell replacement therapy has become a potentially effective treatment option for retinal diseases [1, 2]. RPE, a single layer of cells between the retina and choroid, is essential for preserving photoreceptor function and general retinal health [3]. RPE loss and dysfunction are hallmarks of several retinal degenerative disorders, including Age-Related Macular Degeneration (AMD) [4, 5]. AMD is a progressive eye condition that primarily affects older individuals, leading to the deterioration of the macula, a crucial part of the retina responsible for central vision [6]. AMD can be classified as atrophic damage to the RPE (dry-AMD) or neovascular disruption (wet-AMD) [7]. To manage dry-AMD, patients often use nutritional supplements and make lifestyle changes, such as eating a diet rich in leafy greens and fish [8, 9], avoiding smoking [10], and regularly monitoring their vision. The most common treatment for wet-AMD is the use of Anti-VEGF (vascular endothelial growth factor) injections, including medications such as ranibizumab [11], bevacizumab [12], aflibercept [13], and brolucizumab [14], which inhibit abnormal blood vessel growth and leakage in the retina.

Unlike other cell types in the retina, RPE cells can be easily maintained in culture in controlled environments and are not dependent on synaptic connections to carry out their functions. These characteristics set RPE cells apart from other cell types in the retina and central nervous system, making them desirable candidates for cell transplantation [2]. In recent years, RPE cell transplantation-based therapies have proven to partially restore the photoreceptor visual function in AMD patients [15].

A biological cell membrane, mainly comprised of a lipid bilayer, is a selectively permeable barrier around the cell. In this lipid bilayer, a stable structure is formed by the arrangement of phospholipids with hydrophobic tails and hydrophilic heads [16]. Oxidative stress is a well-documented and prominent contributor to the pathophysiology of AMD [17, 18]. Several studies used hydrogen peroxide (H2O2) as a surrogate for oxidative stress, given its capacity to induce cellular damage by generating Reactive Oxygen Species (ROS) [19,20,21,22,23,24]. H2O2-induced ROS can initiate a process known as lipid peroxidation in cells [25]. In this process, polyunsaturated fatty acids in the lipid bilayer oxidize, forming lipid peroxides. The addition of these peroxides modifies the composition of the membrane by disturbing the phospholipids’ usual packing pattern [26]. The cellular membranes’ capacity to respond to an electric field and store electrical energy is reflected in its dielectric constant [27]. Lipid peroxidation can alter the membrane’s dielectric constant and impair electrical signal response. A notable outcome of this alteration is also observed in the disturbance of membrane conductance [28, 29]. Lipid peroxidation weakens the lipid bilayer’s integrity, which makes it possible for ions like Na+ and K+ to pass through the membrane. The electrochemical balance required for cellular functions, including signaling and osmotic balance, is perturbed by this ion leakage. The cell may depolarize as ions flow erratically across the injured membrane, obstructing regular cellular communication and operation [30].

The capacity of RPE cells to adjust and react in-vitro to these stresses makes them useful to investigate the complex cellular processes underlying AMD pathology. A possible treatment for AMD involves substituting the dead or malfunctioning RPE with healthy cells [15, 31]. This strategy can save photoreceptors, keep the retina’s structural integrity, and eventually protect or restore eyesight. Exploiting the regeneration prospective of these cells is a significant step towards novel therapeutic approaches for retinal diseases, even as current research and clinical trials continue to improve the methods and address issues related to RPE transplantation [32,33,34]. One of the emerging approaches to deliver cells in subretinal space during transplantation is using subretinal injection of RPE cells [35]. This method is preferred due to its ability to place the cells in close proximity to the photoreceptors, which is crucial for effective integration and function. Specifically, the subretinal space, located between the retina and the underlying retinal pigment epithelium, provides an optimal environment for the transplanted cells to interact directly with the photoreceptors, thereby enhancing the potential for successful cell integration and restoration of visual function [36,37,38].

Recent advancements in retinal cell separation methods have significantly improved the efficiency and accuracy of isolating specific cell types for research and clinical applications. For instance, fluorescence-activated cell sorting has been successfully utilized to isolate murine retinal endothelial cells [39] and Induced pluripotent stem cells (iPSC) derived photoreceptors [40] providing high cell yield, viability, and purity suitable for next-generation sequencing and cell replacement therapies. Using electrophysiological properties, DEP effectively enriches astrocyte-biased human neural stem and progenitor cells [41], enabling future experiments on their properties and therapeutic efficacy in neurological diseases. Additionally, label-free microfluidic-based cell separation methods have been employed to separate RPE and iPSC-derived photoreceptor precursor cell lines from mixture as well as to sort RPE and photoreceptor cells from pieces of human retina [42].

Despite all the progress, a number of limitations still stand in the way of the broader clinical use of RPE cell transplantation [43]. A significant challenge is attaining the best possible cell survival and integration in the host retina. Ensuring that RPE cells remain viable and effective over the long term is hampered by their sensitive nature and the possibility of immunological rejection [44, 45]. Moreover, the presence of contaminating cell types may affect the therapeutic efficiency of cell transplantation. Hence, selecting and purifying a homogeneous population of healthy RPE cells is imperative.

Cell transplantation therapies utilize various cell purification techniques, such as density gradient centrifugation [46], immunomagnetic cell sorting [47], and microfluidic technologies [48]. However, obstacles such as cell viability loss, heterogeneity, immunogenicity, procedure expense, and ethical and legal barriers justify developing better methods to improve RPE cell-based treatments [2, 49]. Dielectrophoresis (DEP) based characterization and purification/separation of cells offer solutions to these challenges [50, 51]. DEP provides a high-throughput, non-invasive, and label-free technique for separating target cell populations by manipulating cells according to their dielectric characteristics [51]. DEP can be utilized to purify RPE cells more thoroughly, lowering the possibility of contamination and raising the general standard of the transplanted cells [52,53,54].

In this study, we used DEP to electrically characterize healthy and oxidized RPE cells to investigate the possibilities for separating healthy cells from mixture by dielectrophoresis. To induce the oxidation of RPE cells in-vitro, we used different concentrations of H2O2. The cells were protected by the well-known ROS scavenger N-Acetylcysteine (NAC) to verify that the observed modifications were due to oxidation processes. Furthermore, based on the observed dielectric differences between healthy and oxidized cells, we demonstrated by a simulation model the possibility of separating the healthy cells from suspension containing healthy and oxidized cells.

Dielectrophoresis

The dielectric characteristics of living cells can be measured non-invasively using the DEP technique, enabling the development of methodologies for cell manipulation, characterization, and, most importantly, separation. DEP separation considers the dielectric and size characteristics of the cells and can replace traditional cell separation techniques by improving overall selectivity, speed, and efficiency [48].

When a particle is suspended in a medium with dielectric characteristics that differ from those of the particle, the particle will develop a dipole moment when an alternating electrical field is applied. If the field is non-uniform, a force, called DEP force, \({\overrightarrow{F}}_{DEP}\) is developed. \({\overrightarrow{F}}_{DEP}\) is given by the following formula [55, 56]:

$${\overrightarrow{F}}_{DEP} =2\pi {r}^{3}{\varepsilon }_{0}{\varepsilon }_{med}Re\left[K\left(f\right)\right]\overrightarrow{\nabla }|{E}^{2}|$$

where \(E\) is the strength of the electric field, \({\varepsilon }_{med}\) is the relative electric permittivity of the suspending medium, r is the particle radius, and \({\varepsilon }_{0}\) is the absolute electric permittivity of the vacuum. \(Re\left[K\left(f\right)\right]\) is the real part of the Clausius–Mossotti factor and depends on the electric field’s frequency, \(f\), via the frequency dependence of the complex permittivities of the particle and the medium. The Clausius–Mossotti factor for a homogeneous spherical particle (exhibiting no conductive losses and carrying no charge) is given by [55]:

$$K\left(f\right)= \frac{{\varepsilon }_{p}^{*}- {\varepsilon }_{med}^{*}}{{\varepsilon }_{p}^{*}+2{\varepsilon }_{med}^{*}}$$

The complex permittivity of the particle and suspending medium, denoted as \({\varepsilon }_{p}^{*}\) and \({\varepsilon }_{med}^{*}\), respectively, are dependent on the frequency of the electric field, as per

$${\varepsilon }_{i}^{*}= {\varepsilon }_{i}- \frac{j{\sigma }_{i}}{2\pi f}$$

where \({\sigma }_{i}\) is the corresponding electric conductivity (i represents the particle or the medium). A more complex structure resembling a biological cell, such as a homogenous sphere encircled by a shell (membrane), is the so-called single-shell model. In this case, the particle’s permittivity is given by the expression [55]:

$${\varepsilon }_{p}^{*}= {\varepsilon }_{mem}^{*}\frac{{\left(\frac{r}{r-d}\right)}^{3}+2\left(\frac{{\varepsilon }_{i}^{*}- {\varepsilon }_{mem}^{*}}{{\varepsilon }_{i}^{*}+2{\varepsilon }_{mem}^{*}}\right)}{{\left(\frac{r}{r-d}\right)}^{3}- \left(\frac{{\varepsilon }_{i}^{*}- {\varepsilon }_{mem}^{*}}{{\varepsilon }_{i}^{*}+2{\varepsilon }_{mem}^{*}}\right)}$$

where \(d\) is the shell’s thickness, \(r\) is the particle’s outer radius, and \({\varepsilon }_{i}^{*}\) and \({\varepsilon }_{mem}^{*}\) are the complex permittivities of the interior (cytoplasm) and shell (membrane), respectively. The dependence of \(Re\left[K\left(f\right)\right]\) on frequency \(f\) is called the DEP spectrum of the particle. The DEP spectrum shape is determined by the particle’s geometrical and electrical characteristics, as well as the electrical characteristics of the suspending medium [57]. If the particle moves towards the region of high electric field gradient (which is called positive DEP, p-DEP, reflecting positive values of \(Re\left[K\left(f\right)\right]\)), while if the particle moves opposite the field gradient, then the response is called negative DEP (n-DEP, reflecting negative values of \(Re\left[K\left(f\right)\right]\)) [58]. Those frequencies at which cells do not experience any force, are called cross-over (CO) frequencies. The cells' electric parameters (membrane/cytoplasm permittivity and conductivity) and crossover (CO) frequencies can be computed based on the DEP spectra. Increasing the membrane permittivity shifts the first CO towards lower values, increasing membrane conductivity shifts the plateau of the n-DEP at low frequencies towards higher values, while increasing cytosol conductivity increases the p-DEP plateau and shifts the second CO towards the higher values (Fig. OR 8).

Intracellular ROS formation, the role of antioxidant NAC

The intracellular primary mechanism of ROS generation (e.g., superoxide anion, hydrogen peroxide, hydroxyl radicals, and singlet molecular oxygen) is the production of free radicals while forming H2O from O2 [59]:

Superoxide anion (O2•−), a free radical that is the most abundantly intracellularly present and a precursor to other more aggressive ROS [60], initiates the intracellular Fenton reaction by reducing ferric iron (Fe3+) to its redox-active form (Fe2+) [61]:

$$\begin{array}{c} \overset{\text{Fenton reaction}}{Fe^{2+}+H_{2}O_{2}\rightarrow Fe^{3+}+\cdot OH+OH^{-}} \qquad\qquad \overset{\text{Reduction of Fe}^{3+}}{Fe^{3+}+O\cdot_{\bar{2}}\rightarrow Fe^{2+}+O_2}\\ \\ \overset{\text{Haber-Weiss reaction}}{O\cdot_{\bar{2}}+H_2O_2\rightarrow\cdot OH+O_2+OH^-}\end{array}$$

The overall outcome of these processes is the intracellular presence of a mixture of all these ROS species. Since H2O2 is uncharged and a non-radical ROS, it can readily permeate across the various cellular compartments. A low physiological amount of H2O2 is constantly present in cells and plays a crucial role as a signaling molecule in regulating cytosolic redox activity [62]. Under oxidative stress, if the antioxidant defense mechanism cannot offset the ROS effects, H2O2 may undergo homolitical cleavage, yielding highly reactive hydroxyl radicals (\({}{}^{.}\text{OH}\)) and hydroxide anions.

NAC is a synthetic precursor of intracellular glutathione and cysteine. Its anti-ROS effect comes from its ability to scavenge free radicals directly through thiols’ redox potential or indirectly by raising glutathione levels in the cells [63]. Studies have reported using NAC as a ROS scavenger in drug-induced cell apoptosis [64].

Materials and methods

Cells and chemicals

All the experiments reported in this study were done using a rat retinal pigment epithelial cell line (BPEI-1, Kerafast). To obtain pigmented, epithelioid type of cells, BPEI-1 was grown in Dulbecco’s Modified Eagle’s Medium (DMEM, Sigma D5796, UK) supplemented with 5% fetal bovine serum (Sigma F7524, Brazil) in a humidified incubator at 5% CO2 and 37 °C [65]. The cells were routinely passaged every 2–3 days by washing the cell layer with 0.9% NaCl and detaching them using 4Na+-trypsin (Sigma T4174, USA). The experiments were conducted when the cells achieved a steady division rate of approximately 2 × /24 h (starting from passage 15). Based on our observation, the cells maintained a constant division rate until passages 55–60, which covers the experiments in this study. After counting them with a tabletop cell counter, the cell concentrations were adjusted according to each experimental category (BioRad TC10 Automated Cell Counter, USA).

H2O2 and NAC treatments

To induce the conditions of oxidative stress to the BPEI-1 cells, H2O2 (30%, Honeywell Fluka 31,642, Germany) was used. N-Acetylcysteine (Merck A7250, 100 mM water stock solution) was used as a ROS scavenger. Before each experiment, the working concentrations of H2O2 (10, 25, 50, 75, 100, 150, 200 µM) and NAC (0.5, 1.0, 2.5 mM) were freshly diluted from the stocks in DMEM. The H2O2 and NAC were added simultaneously in all experiments in which antioxidant protection was wanted. No preincubation was used as DMEM does not contain any chemical species to facilitate the external Fenton reaction.

Cell viability and morphology evaluation: MTS assay and microscopy

The cell viability was measured using an MTS assay (CellTiter 96® AQueous G3582, Promega, USA). 20,000 cells/well were seeded in a 96-well plate (TPP 92696, Switzerland). After 24 h of growth, cells were incubated for another 24 h with the working concentrations of H2O2 and/or NAC (as specified in chapter 2.2). After incubation, each well was carefully washed twice with DMEM, and then 150 µL MTS was added (1:6 in DMEM growth medium). The cells were kept for 2 h in the incubator, and then their absorbance was measured at 492 nm in a plate reader (Awareness Technology, USA). The absorbance was expressed as a viability percentage by normalizing it to the Controls.

For microscopy evaluations, the cells were seeded in 6-well plates (Orange Scientific, Belgium) to reach full confluence in about 72 h. After 24 h from seeding, the cells were exposed to H2O2 and/or NAC at the following final concentrations: Control (0 µM H2O2 + 0.0 mM NAC), 50 µM H2O2, 100 µM H2O2, 100 µM H2O2 + 0.5 mM NAC, 100 µM H2O2 + 1.0 mM NAC, 100 µM H2O2 + 2.5 mM NAC. These experimental groups were chosen because they cover a range of concentrations in which the effect of the peroxidation and protection are observed on the cell viability. Microscopic images were acquired for these experimental conditions after 24 and 48 h (AxioVert 200, Carl Zeiss, Germany).

Monitoring cell proliferation: Real-Time Cell Analysis (RTCA)

After measuring the RTCA (xCELLigence RTCA DP, Germany) baseline in the growth medium, 12,000 cells were seeded in each well of a dedicated 16-well plate (E16, xCELLigence, Germany). The experiments were performed using H2O2 (0, 50, and 100 µM) supplemented by NAC (0.0, 0.5, 1.0, 2.5 mM). The RTCA was set to measure the Cell Index (CI) value (a dimensionless parameter computed based on the impedance variations induced by the cell attachment to a gold electrodes array) every 10 min for 72 h. The H2O2 and NAC were added 23–24 h after seeding without removing the existing medium, and the RTCA measurement was resumed.

DEP spectra recordings

DEP experiments were performed using the OpenDEP platform, encompassing the DEP chip (OpenDEP LoC) and the software with which the data was analyzed (OpenDEP software) [66]. Fig. OR 7 presents an example of experimental images to be processed in the OpenDEP software. For each experiment, the cells from the same passage were split in T75 flasks (TPP 90076, Switzerland) and allowed to grow until approximately 40% confluency. The cells were treated with the working experimental concentrations of H2O2 (0 µM, 25 µM, 50 µM, 100 µM) and NAC (0 mM, 0.5 mM, 1.0 mM, 2.5 mM) by replacing the growth medium. Then after 24 h, the cells were detached using trypsin, suspended in DMEM, and centrifuged for 5 min at 300 g at room temperature. After discarding the supernatant, the cell pellet was gently washed three times using a sucrose-based low conductivity buffer (pH 7.4, 0.01 S/m, 300 mOsm/kg) without detaching it from the bottom of the tube. Finally, the pellet was resuspended in the same buffer and the cell sizes were measured (no differences between the experimental groups were observed – data not shown). The low conductivity buffer was obtained by mixing a 300 mM sucrose solution (pH 7.4, 0.002 S/m, 300 mOsm/kg) with a saline sucrose solution (250 mM sucrose, 8 mM Na2HPO4, 2 mM KH2PO4, 1 mM MgCl2, pH 7.4, ~ 0.128 S/m, 300 mOsm/ kg) at a ratio necessary to achieve the 0.01 S/m conductivity. Finally, a cell concentration of 1 × 107 cells/mL was adjusted (providing a similar level of grayness as the one used in [66]), and the cells' average size was measured before performing DEP measurements. The 0.01 S/m buffer conductivity was chosen as an optimal value after performing preliminary test with different conductivities (see Fig. OR 1 in Online Resource). The \(Re\left[K\left(f\right)\right]\) were recorded at 20 frequencies between 1 kHz and 75 MHz (10 Vpp). The electric parameters of cells (membrane permittivity and conductivity and cytosol conductivity) were computed from each individual DEP spectrum and are represented as means ± SD. The DEP spectra shown in the graphs were obtained by fitting the average of all the spectra belonging to specified experimental conditions (this is why the first CO frequency depicted on the computed spectra may slightly differ from the its mean value shown in the bar graphs). DEP results for 25 µM H2O2 and 0.5 mM, 2.5 mM NAC are only presented in Fig. OR 4 and 5.

DEP simulations

Autodesk Fusion 360 was utilized to design the microfluidic channel and DEP electrodes, while COMSOL Multiphysics (Fluid flow, Electric currents, Particle tracing modules, 2D space dimension) was employed to simulate electric fields, fluid dynamics, and particle tracing. The model of the microfluidic channel remains theoretical, with no physical prototype yet constructed. Detailed input parameters for the simulation are provided in Table OR 1. For the electrical characteristics of the cells, calculations were based on the acquired experimental DEP spectra. The buffer conductivity, determined to be optimal for generating the maximum p-DEP force, was set at 0.01 S/m. The frequency selected for simulating DEP-based separation corresponded to the CO frequency of target cells (healthy) while ensuring the treated cells experienced a p-DEP effect. The simulation also accounted for the standard deviation in both the electrical properties and the dimensions of the cells. Consequently, each simulated particle was unique, possessing a set of characteristics (such as cell size, membrane permittivity, and conductivity, cytoplasm conductivity) that fell within the error margins of the measured or computed values. To closely replicate real-world conditions, particles were introduced into the channel in a random distribution pattern.

Data processing and statistical analysis

For microscopy experiments, 3 images for each experimental condition were acquired. The MTS tests were performed in a minimum 4 technical replicates for each experimental condition. The CI and DEP spectra were recorded in 2 technical replicates belonging to 2 and 3 biological replicates, respectively. Results are expressed as means ± Standard Deviation (SD). The Shapiro–Wilk analysis was used to check for the normality of data distribution, and the Student t-test was used to test the significance of the differences (p < 0.05*, p < 0.01**, p < 0.001***). All statistical tests were performed using Python (NumPy, SciPy, and matplotlib libraries). Microsoft Excel and OpenDEP software were used to process DEP data.

Results

Cell morphology and viability test: Microscopy and MTS assay

Microscopic images obtained after 24 h (Fig. 1a-f) and 48 h (Fig. OR 2) of cells exposure to H2O2 ± NAC showed distinct morphological alterations in BPEI-1 cells.

Fig. 1
figure 1

a-f Microscopic images of BPEI-1 rat RPE cells exposed for 24 h to different concentrations of H2O2 and NAC after 24 h of cell growth. g Cells viabilities evaluated by MTS assay for the similar conditions, the viability is expressed as % normalized to the Control (0 µM H2O2, 0.0 mM NAC), mean ± SD

Full size image

In Fig. 1a-c, one can observe that more cells were getting round while increasing the H2O2 concentrations in the absence of NAC, meaning that more and more cells were detaching from the plate bottom. This is a consequence of the concentration-dependent toxic effect of H2O2. When using 100 µM H2O2 in the presence of different NAC concentrations, the toxic effect of H2O2 was diminished (Fig. 1d-f). These results correlate to the cell viabilities evaluated by the MTS assay (Fig. 1g). In the absence of NAC, the toxic effect of peroxide is reflected in a progressive cell viability decrease with increasing peroxide concentration (red, blue, and yellow points at 0.0 mM NAC). This effect is diminished in the presence of NAC. The efficiency of the protective effect of NAC reaches a maximum at 1.0 mM. Complete data on microscopy and MTS tests are available in Online Resource Fig. OR 2 and 3, respectively.

Real-time investigation of cell responsiveness to H2O2 and NAC

Real-time cell analysis (RTCA) is a technique that records cellular behavior, such as adhesion, proliferation, viability, and morphology, in real time in a non-invasive manner [67]. Comparing RTCA to standard end-point tests (e.g., MTS), the time response observation of cell behavior is more potent and insightful. The RTCA curves of BPEI-1 cells were acquired under the same experimental conditions (H2O2 and NAC concentrations) as in the microscopy and MTS tests. To highlight the effect of reagents, all the raw curves were normalized at a time point before their addition (at 23 h). In the case of the Control, one can see that the cell growth resumed after several hours from the addition of growth medium (red curve in Fig. 2) until the confluence was reached (~ 55 h), followed by cell death (reflected in a decrease of CI) due to overpopulation. When adding 100 µM H2O2, the cells began to die without any subsequent recovery (lime curve in Fig. 2). After adding either 0.5 or 1 mM NAC, the CI decreased (until ~ 45 h) in a dose-dependent manner, indicating the cell detachment and death, followed by an increase corresponding to the cell recovery due to the antioxidant effect of NAC. The cell recovery kinetics were slower in both cases than in the Control one. At 2.5 mM NAC, the CI decreased (although less than in the case of H2O2 alone), and the recovery appeared much later, suggesting a toxicity of NAC at high concentration (teal curve in Fig. 2, data with 50 µM H2O2 is available in Online Resource Fig. OR 4).

Fig. 2
figure 2

Cell Index curves monitoring BPEI-1 cells proliferation in different experimental conditions: Control (0 µM H2O2, 0.0 mM NAC), 100 µM H2O2 (without NAC), and 100 µM H2O2 and 3 NAC concentrations. The reagents were added at 23 h after seeding and the monitoring continued for other 48 h. The Normalization function of the xCELLigence software was used to normalize all the curves at the time point 23 h. Curves represent the mean (± SD) of normalized CI value of 2 biological replicates worked in 2 wells each

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The combined results on cell viability allowed us to optimize the H2O2 and NAC concentrations to be used in the DEP experiments: 100 µM H2O2 and 1.0 mM NAC. For instance, the oxidized cells kept a viability around 80% (as shown by MTS assay), which is a recommended level of viable cells for an experimental measurement to be performed [68]. The minimum antioxidant concentration to fully protect the cells (100% viability on MTS assay, CI of RTCA at the levels of Control) was 1.0 mM NAC.

Dielectrophoretic characterization of cells exposed to H2O2 and NAC

DEP experiments were conducted in 0.01 S/m sucrose-based buffer, which was found appropriate for calculating cells dielectric parameters (see Fig. OR 1 in Online Resource).

DEP experiments were performed on BPEI-1 cells exposed 24 h to different H2O2 concentrations. In Fig. 3, data for 0, 50 and 100 µM H2O2 are shown (data for all H2O2 concentrations are available in Online Resource Fig. OR 5). One can observe that the DEP spectra are changing in terms of plateau levels and CO frequencies (Fig. 3a). A statistically significant shift of the first CO frequency towards lower values (Fig. 3b) was observed when cells were exposed to H2O2 but not in a concentration-dependent manner (see Fig. OR 5b in Online Resource). This shift is due to increased negative plateau levels (towards values closer to 0) at frequencies below the first CO.

Fig. 3
figure 3

DEP analysis of BPEI-1 cells exposed to 0, 50, and100 µM H2O2. a DEP spectra. Computed cell parameters (mean ± SD): b first CO frequency, c cytoplasm conductivity and (d) membrane permittivity

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These modifications reflect changes in the cell electric parameters. The membrane permittivity increased with increasing H2O2 concentrations (Fig. 3d and OR 5d), while cytoplasmic conductivity showed no significant variation (Fig. 3c).

The DEP spectra of BPEI-1 cells exposed to 100 µM H2O2 supplemented with NAC (0.5, 1.0, 2.5 mM) were also recorded. At 1.0 mM NAC, the first CO frequency was between H2O2 exposed cells and Control. Also, the plateau value of the DEP spectrum in the frequency domain below the first CO was between those of Controls and H2O2-exposed cells (Fig. 4a, b). The computed membrane permittivity values were significantly closer to the values of the Controls in the presence of 1.0 mM NAC (Fig. 4d).

Fig. 4
figure 4

DEP analysis of BPEI-1 cells exposed to 0, 100 µM H2O2 and/or 1.0 mM NAC. a DEP spectra. Computed cell parameters (mean ± SD): b first CO frequency, c cytoplasm conductivity and (d) membrane permittivity

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The other parameters (cytoplasm and membrane conductivities) showed no significant modifications (Fig. 4c and OR 6e). These data show that the presence of NAC prevents the modification of membrane permittivity by peroxide on BPEI-1 cells. DEP data for 100 µM H2O2 supplemented with all NAC concentrations is available in Online Resource Fig. OR 6.

Simulations for cells separation

A COMSOL simulation was performed on a theoretical microfluidic-based DEP separation chip using the electric parameters obtained from the acquired DEP spectra (see Online Resource Table OR 1 for simulation parameters). As shown in Fig. 5, the chip consists of two ‘Y’ shaped channels for microfluidic inlets and outlets linked by a central channel where the DEP electrodes are located. Cells suspension (a mixture of treated and healthy cells) and DEP buffer are injected separately through the two inlets at the same precise flow rate to ensure a laminar flow. Each simulated particle inserted into the channel was given a unique set of parameters (size and electric parameters of membrane and cytosol), randomly distributed within the standard deviation of the specific population (Control or Treated) as resulted from population DEP experiments processing. This means that each particle in the simulation is unique.

Fig. 5
figure 5

Simulations in the DEP separation chip model of: a flow rate, b electric field intensity, c, d separation of the Control (healthy) cells from mixtures of healthy and cells treated with 50 and 100 µM H2O2, respectively. The DEP field frequency was 28.941 kHz, which is the first CO frequency of the Control cells

Full size image

The buffer pushes the cells towards that side of the central channel where cells were injected. When the cells are exposed to DEP in the central channel at the CO frequency of control cells, only those treated with H2O2 experience a DEP force (either n-DEP or p-DEP) and will deviate towards the outlet opposite the inlet where the cells were injected. Our simulations showed that the healthy cells can be separated from those treated with a 100% yield (Fig. 5c, d) for both cases of H2O2 treatment (50 and 100 µM).

Discussion

In this study, we presented an approach to obtain an in-vitro model for studying AMD. Our DEP results showed that increasing the degree of membrane peroxidation (by increasing the H2O2 concentration) progressively increases the cell membrane permittivity. The fact that these modifications are suppressed to some extent when using NAC allows us to assume that the increase in membrane permittivity is indeed a consequence of oxidation processes. This agrees with findings regarding membrane capacitance variations due to lipid peroxidation induced by water radiolysis and the photodynamic generation of singlet oxygen when working on model planar lipid membranes [28, 29].

Oxidative stress induced by ROS can directly modify cellular proteins and lipids to produce molecules with hydroxyl, carbonyl, or epoxide groups. Free-radical ROS can also take up hydrogen from proteins and membrane lipids and form new radicals. Particularly concerning lipids, hydrogen abstraction of unsaturated acyl chains can start a chain reaction that spreads to the other lipids in the bilayer. Many chemical processes, including cyclization, rearrangement, and cleavage, frequently occur following oxidation. This could lead to the formation of different lipid derivatives, such as oxidized lipids with a carboxylic acid in one of their acyl chains, as well as non-fragmented and fragmented species [69, 70]. According to the known lipid composition of RPE rat cells [71] there are present many polyunsaturated fatty acids as: 18:1, 18:2ω6, 20:0, 20:2, 22:0, 20:4ω6, 22:4, 22:5, 22:6ω3. They can be the target of the peroxidation process. This leads to increased membrane permittivity by enhancing membrane order and viscosity, decreasing bilayer thickness, modifying fluidity, and finally increasing ion permeability, which can explain the increased membrane permittivity. These modifications contribute to cell damage by compromising the native architecture of the membrane and disturbing the flow of ions and electrical signals needed for normal cell function. The accumulation of oxidized products within the cell membrane moiety is expected to influence the activity of the ion channels, carriers, and pumps, leading to cell malfunction and eventually cell death [28, 72].

DEP is a good method to characterize the impact of peroxidation in terms of electrical properties of cell membrane and cytosol. To fit the experimental data obtained on eukaryotic spherical cells (like in our experiments), the single shell model is the most appropriate. This simplification represents a limitation of the method. To highlight all the damages induced by oxidation, like DNA breaking or metabolic activity impairment, more complex studies or models are necessary. It was observed that the shift of the first CO frequency towards lower values when cells were exposed to H2O2 was not depending on the concentration of the peroxide, being rather “all or nothing” response. Future experiments would be to quantify the degree of peroxidation using specific biochemical methods.

Conclusions

In this study, using an in-vitro AMD model, we demonstrated the possibility to characterize and separate healthy/peroxidized BPEI-1 RPE cells using a DEP based method. We showed that DEP provides CO frequencies of healthy and peroxidized BPEI-1 cells, accurate enough to be exploited for separation procedures, representing the main scope of our study. We showed by simulations that this can potentially aid in separating healthy BPEI-1 cells from mixtures of oxidized and healthy cells in view of transplantation procedures. Thus, DEP separation could be a solution to obtain a high yield of homogenous healthy cell population. DEP-based experimental characterization of healthy and oxidized RPE cells and simulations for their separation were priced for applications in modern personalized cell replacement therapies.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

RPE:

Retinal Pigment Epithelial

AMD:

Age-Related Macular Degeneration

VEGF:

Vascular Endothelial Growth Factor

H2O2 :

Hydrogen Peroxide

ROS:

Reactive Oxygen Species

iPSC:

Induced pluripotent stem cells

DEP:

Dielectrophoresis

p-DEP:

Positive Dielectrophoresis

n-DEP:

Negative Dielectrophoresis

CO:

Crossover

NAC:

N-Acetylcysteine

DMEM:

Dulbecco’s Modified Eagle’s Medium

CI:

Cell Index

RTCA:

Real-Time Cell Analysis

OR:

Online Resource

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Acknowledgements

Not applicable.

Funding

This project has received funding from the European Union’s Horizon 2020 research innovation program under the Marie Skłodowska-Curie grant agreement No 861423, and partially from UEFISCDI project PN-III-P2-2.1-PED-2021–0451, contract no. 596PED⁄2022.

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Author notes

  1. Dharm Singh Yadav and Ioan Tivig these authors have equally contributed.

Authors and Affiliations

  1. Biophysics and Cellular Biotechnology Department, Faculty of Medicine, Carol Davila University of Medicine and Pharmacy, 8 Eroii Sanitari blvd., Bucharest, 050474, Romania

    Dharm Singh Yadav, Ioan Tivig, Tudor Savopol & Mihaela G. Moisescu

  2. Excellence Center for Research in Biophysics and Cellular Biotechnology, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania

    Ioan Tivig, Tudor Savopol & Mihaela G. Moisescu

Authors
  1. Dharm Singh Yadav
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Dharm Singh Yadav, Ioan Tivig, Mihaela G. Moisescu, and Tudor Savopol. The first draft of the manuscript was written by Dharm Singh Yadav and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Tudor Savopol.

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Yadav, D.S., Tivig, I., Savopol, T. et al. Dielectrophoretic characterization of peroxidized retinal pigment epithelial cells as a model of age-related macular degeneration. BMC Ophthalmol 24, 340 (2024). https://doi.org/10.1186/s12886-024-03617-0

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BMC Ophthalmology

ISSN: 1471-2415

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