A computational modeling and analysis in cell biological dynamics using electric cell-substrate impedance sensing (ECIS)

3D bio-printing-based vascular-microtissue electrochemical biosensor for fish parvalbumin detection

A novel 3D bio-printing vascular microtissue biosensor was developed to detect fish parvalbumin quickly. The graphite rod electrode was modified with gold and copper organic framework (Cu-MOF) to improve the sensor properties. Polydopamine-modified multi-wall carbon nanotubes (PDA-MWCNT) were mixed with gelatin methacryloyl (GelMA) to prepare a conductive hydrogel. The conductive hydrogel was mixed with mast cells and endothelial cells to produce a bio-ink for 3D bioprinting. High throughput and standardized preparation of vascular microtissue was performed by stereolithography 3D bioprinting. The vascular microtissue was immobilized on the modified electrode to construct the microtissue sensor. The biosensor's peak current was positively correlated with the fish parvalbumin concentration, and the detection linear concentration range was 0.1 ∼ 2.5 μg/mL. The standard curve equation was IDPV(μA) = 31.30 + 5.46 CPV(μg/mL), the correlation coefficient R2 was 0.990 (n = 5), and the detection limit was 0.065 μg/mL. These indicated a biomimetic microtissue sensor detecting fish parvalbumin has been successfully constructed.

Use of Discrete Wavelet Transform to Assess Impedance Fluctuations Obtained from Cellular Micromotion

Electric cell–substrate impedance sensing (ECIS) is an attractive method for monitoring cell behaviors in tissue culture in real time. The time series impedance fluctuations of the cell-covered electrodes measured by ECIS are the phenomena accompanying cellular micromotion as cells continually rearrange their cell–cell and cell–substrate adhesion sites. Accurate assessment of these fluctuations to extract useful information from raw data is important for both scientific and practical purposes. In this study, we apply discrete wavelet transform (DWT) to analyze the concentration-dependent effect of cytochalasin B on human umbilical vein endothelial cells (HUVECs). The sampling rate of the impedance time series is 1 Hz and each data set consists of 2048 points. Our results demonstrate that, in the Daubechies (db) wavelet family, db1 is the optimal mother wavelet function for DWT-based analysis to assess the effect of cytochalasin B on HUVEC micromotion. By calculating the energy, standard deviation, variance, and signal magnitude area of DWT detail coefficients at level 1, we are able to significantly distinguish cytotoxic concentrations of cytochalasin B as low as 0.1 μM, and in a concentration-dependent manner. Furthermore, DWT-based analysis indicates the possibility to decrease the sampling rate of the micromotion measurement from 1 Hz to 1/16 Hz without decreasing the discerning power. The statistical measures of DWT detail coefficients are effective methods for determining both the sampling rate and the number of individual samples for ECIS-based micromotion assays.

Comparative in vitro Studies of the Topoisomerase I Inhibition and Anticancer Activities of Metallated N-Confused Porphyrins and Metallated Porphyrins

Using the original approach, a series of metallated N-confused porphyrins and metallated porphyrins have been synthesized and characterized. For all the synthesized porphyrins, in vitro studies of cytotoxic activity against K562, U937, HL-60, Jurkat, A549 and HeLa cancer cell lines, the ability to induce apoptosis and effects on the cell cycle as well as the kinetics of proliferative activity of porphyrins and their respective metallated complexes in real time have been developed. The inhibitory activity of metallated porphyrins against human topoisomerase I and the possible mechanism of inhibition have been carried out by modelling using molecular docking.

VEGI174 protein and its functional domain peptides exert antitumour effects on renal cell carcinoma

Vascular endothelial growth inhibitor (VEGI) has been identified as an anti‑angiogenic cytokine. However, the effects of VEGI174 protein, and its functional domain peptides V7 and V8, on renal cell carcinoma (RCC) remain unknown. In the present study, the protein and peptides were biosynthesised as experimental agents. The A498 and 786‑O RCC cell lines, and an established mouse xenograft model, were separately treated with VEGI174, V7 or V8. Cellular functions, including proliferation, migration and invasion, were subsequently detected. Cell migration and invasion were monitored using the xCELLigence system. Furthermore, tumour growth and mouse behaviours, including mobility, appetite and body weight, were assessed. The results demonstrated that VEGI174, V7 and V8 inhibited the proliferation, migration and invasion of A498 and 786‑O cell lines when administered at concentrations of 1 and 100 pM, 10 nM and 1 µM. The inhibitory effects exhibited dose‑ and time‑dependent antitumour activity. Furthermore, VEGI174, V7 and V8 inhibited tumour growth in A498 and 786‑O xenograft mice. In the A498 xenografts, the tumour growth inhibition (TGI) rates in the VEGI174‑, V7‑ and V8‑treated groups were 71, 20 and 31%, respectively. In the 786‑O xenografts, the TGI rates in the VEGI174‑, V7‑ and V8‑treated groups were 34, 26 and 31%, respectively. There was no significant loss in body weight and no cases of mortality were observed for all treated mice. In conclusion, VEGI174, V7 and V8 exhibited potential antitumour effects and were well tolerated in vivo. V7 and V8, as functional domain peptides of the VEGI174 protein, may be studied for the future treatment of RCC.

Electrical Impedance Monitoring of C2C12 Myoblast Differentiation on an Indium Tin Oxide Electrode

Electrical cell-substrate impedance sensing is increasingly being used for label-free and real-time monitoring of changes in cell morphology and number during cell growth, drug screening, and differentiation. In this study, we evaluated the feasibility of using ECIS to monitor C2C12 myoblast differentiation using a fabricated indium tin oxide (ITO) electrode-based chip. C2C12 myoblast differentiation on the ITO electrode was validated based on decreases in the mRNA level of MyoD and increases in the mRNA levels of myogenin and myosin heavy chain (MHC). Additionally, MHC expression and morphological changes in myoblasts differentiated on the ITO electrode were comparable to those in cells in the control culture dish. From the monitoring the integration of the resistance change at 21.5 kHz, the cell differentiation was label-free and real-time detectable in 30 h of differentiation (p < 0.05).

Combinatorial approaches to evaluate nanodiamond uptake and induced cellular fate

Nanodiamonds (NDs) are an emerging class of engineered nanomaterials that hold great promise for the next generation of bionanotechnological products to be used for drug and gene delivery, or for bio-imaging and biosensing. Previous studies have shown that upon their cellular uptake, NDs exhibit high biocompatibility in various in vitro and in vivo set-ups. Herein we hypothesized that the increased NDs biocompatibility is a result of minimum membrane perturbations and their reduced ability to induce disruption or damage during cellular translocation. Using multi-scale combinatorial approaches that simulate ND-membrane interactions, we correlated NDs real-time cellular uptake and kinetics with the ND-induced membrane fluctuations to derive energy requirements for the uptake to occur. Our discrete and real-time analyses showed that the majority of NDs internalization occurs within 2 h of cellular exposure, however, with no effects on cellular viability, proliferation or cellular behavior. Furthermore, our simulation analyses using coarse-grained models identified key changes in the energy profile, membrane deformation and recovery time, all functions of the average ND or ND-based agglomerate size. Understanding the mechanisms responsible for ND-cell membrane interactions could possibly advance their implementation in various biomedical applications.

A quantitative cell modeling and wound-healing analysis based on the Electric Cell-substrate Impedance Sensing (ECIS) method

In this paper, a quantitative modeling and wound-healing analysis of fibroblast and human keratinocyte cells is presented. Our study was conducted using a continuous cellular impedance monitoring technique, dubbed Electric Cell-substrate Impedance Sensing (ECIS). In fact, we have constructed a mathematical model for quantitatively analyzing the cultured cell growth using the time series data directly derived by ECIS in a previous work. In this study, the applicability of our model into the keratinocyte cell growth modeling analysis was assessed first. In addition, an electrical "wound-healing" assay was used as a means to evaluate the healing process of keratinocyte cells at a variety of pressures. Two innovative and new-defined indicators, dubbed cell power and cell electroactivity, respectively, were developed for quantitatively characterizing the biophysical behavior of cells. We then employed the wavelet transform method to perform a multi-scale analysis so the cell power and cell electroactivity across multiple observational time scales may be captured. Numerical results indicated that our model can well fit the data measured from the keratinocyte cell culture for cell growth modeling analysis. Also, the results produced by our quantitative analysis showed that the wound healing process was the fastest at the negative pressure of 125mmHg, which consistently agreed with the qualitative analysis results reported in previous works.

Wavelet-based multiscale analysis of bioimpedance data measured by electric cell-substrate impedance sensing for classification of cancerous and normal cells

The paper presents a study to differentiate normal and cancerous cells using label-free bioimpedance signal measured by electric cell-substrate impedance sensing. The real-time-measured bioimpedance data of human breast cancer cells and human epithelial normal cells employs fluctuations of impedance value due to cellular micromotions resulting from dynamic structural rearrangement of membrane protrusions under nonagitated condition. Here, a wavelet-based multiscale quantitative analysis technique has been applied to analyze the fluctuations in bioimpedance. The study demonstrates a method to classify cancerous and normal cells from the signature of their impedance fluctuations. The fluctuations associated with cellular micromotion are quantified in terms of cellular energy, cellular power dissipation, and cellular moments. The cellular energy and power dissipation are found higher for cancerous cells associated with higher micromotions in cancer cells. The initial study suggests that proposed wavelet-based quantitative technique promises to be an effective method to analyze real-time bioimpedance signal for distinguishing cancer and normal cells.

Cellular micromotion monitored by long-range surface plasmon resonance with optical fluctuation analysis

Long-range surface plasmon resonance (LRSPR) is a powerful biosensing technology due to a substantially larger probing depth into the medium and sensitivity, compared with conventional SPR. We demonstrate here that LRSPR can provide sensitive noninvasive measurement of the dynamic fluctuation of adherent cells, often referred to as the cellular micromotion. Proof of concept was achieved using confluent layers of 3T3 fibroblast cells and MDA-MB-231 cancer cells. The slope of the power spectral density (PSD) of the optical fluctuations was calculated to determine the micromotion index, and significant differences were measured between live and fixed cell layers. Furthermore, the performances of LRSPR and conventional surface plasmon resonance (cSPR) were compared with respect to micromotion monitoring. Our study showed that the micromotion index of cells measured by LRSPR sensors was higher than when measured with cSPR, suggesting a higher sensitivity of LRSPR to the micromotion of cells. To investigate further this finding, simulations were conducted to establish the relative sensitivities of LRSPR and cSPR to membrane fluctuations. Increased signal intensity was predicted for LRSPR in comparison to cSPR, suggesting that membrane fluctuations play a significant role in the optical micromotion measured in LRSPR. Analogous to cellular micromotion measured using impedance techniques, LRSPR micromotion has the potential to provide important biological information on the metabolic activity and viability of adherent cells.

Real-time analysis of the effects of toxic, therapeutic and sub-therapeutic concentrations of digitoxin on lung cancer cells

Digitoxin belongs to a naturally occurring class of cardiac glycosides (CG); digitoxin is clinically approved for heart failure and known for its anti-cancer effects against non-small lung cancer cells (NSCLC). However, concerns associated with its narrow therapeutic index and its concentration-dependent mechanism of action are rising. Thus, before digitoxin implementation in designing and developing safer and more effective CG-based anti-cancer therapies, its pharmacological and safety profiles need to be fully elucidated. In this research we used a combinatorial approach to evaluate the anti-cancer mechanisms of digitoxin in real-time. Our approach employed a non-invasive electric cell impedance sensing technique as a proxy to monitor NSCLC behavior post-exposure to toxic, therapeutic and sub-therapeutic concentrations of the drug. By developing structure-function combinatorial relations we showed that digitoxin targets cancer cells in a time and dose-dependant manner by activating pro-apoptotic and anti-proliferative signaling cascades that results in strengthening cellular adhesion and sequestration of key regulatory proliferation protein from the nucleus.

Real-time monitoring of photocytotoxicity in nanoparticles-based photodynamic therapy: a model-based approach

Nanoparticles are widely suggested as targeted drug-delivery systems. In photodynamic therapy (PDT), the use of multifunctional nanoparticles as photoactivatable drug carriers is a promising approach for improving treatment efficiency and selectivity. However, the conventional cytotoxicity assays are not well adapted to characterize nanoparticles cytotoxic effects and to discriminate early and late cell responses. In this work, we evaluated a real-time label-free cell analysis system as a tool to investigate in vitro cyto- and photocyto-toxicity of nanoparticles-based photosensitizers compared with classical metabolic assays. To do so, we introduced a dynamic approach based on real-time cell impedance monitoring and a mathematical model-based analysis to characterize the measured dynamic cell response. Analysis of real-time cell responses requires indeed new modeling approaches able to describe suited use of dynamic models. In a first step, a multivariate analysis of variance associated with a canonical analysis of the obtained normalized cell index (NCI) values allowed us to identify different relevant time periods following nanoparticles exposure. After light irradiation, we evidenced discriminant profiles of cell index (CI) kinetics in a concentration- and light dose-dependent manner. In a second step, we proposed a full factorial design of experiments associated with a mixed effect kinetic model of the CI time responses. The estimated model parameters led to a new characterization of the dynamic cell responses such as the magnitude and the time constant of the transient phase in response to the photo-induced dynamic effects. These parameters allowed us to characterize totally the in vitro photodynamic response according to nanoparticle-grafted photosensitizer concentration and light dose. They also let us estimate the strength of the synergic photodynamic effect. This dynamic approach based on statistical modeling furnishes new insights for in vitro characterization of nanoparticles-mediated effects on cell proliferation with or without light irradiation.