Coupled impedance & field potential data analysis of in vitro cardiomyocyte assays

Présentation PosterInternational audienc

Mixed-effects modeling for concentration effect profiling in cardiomyocyte contractility assays

Présentation PosterInternational audienceBackground. With the advent of new realtime technologies such as impedance assays, extracellular field potential measurement and optical sensing for in vitro cardiac safety screening studies, researchers have now to frequently deal with analyzing voluminous amounts of complex time responses. In this context, main issues are to speed up the data analysis process and to extract accurate information for cardiotoxicity profiling. Objectives. A first objective is the development of an innovative computational method able to globally process a large set of in vitro cardiac signals (provided by 96, 384 and 1536-well microplates) instead of analyzing them once at a time. Such a statistical population approach has the advantage the account for the common characteristics between the individual responses. A second objective is to handle qualitative factors (type of cardiomyocytes, compounds and media, etc.) in the computational process. Methods. The proposed estimation method relies on the combination of a dynamic system identification method and a mixed-effect modeling technique. An output-error polynomial model structure is used for the system identification step and a stochastic approximation expectation maximization is implemented for the estimation of the hyperparameters. Input signals to be analyzed are the contractility amplitudes of cardiomyocytes submitted to compounds to be tested. Impedance signals and contractility amplitude were provided by a CardioExcyte96 system (Nanion Technologies). human iPSC-derived cardiomyocytes were provided by Cellartis Takara with 30,000 cells per well. Results. Our data-driven profiling method extracted four parameters that completely fit the contractility time variations and fully characterize the effect of compound concentration on the contractility amplitude. The proposed method not only estimates the values of the model parameters but also their uncertainty distribution. The latter allows to compute p-values associated with each effect.Conclusion. We show that the population-based estimation method developed in this study is suited to the fully characterize dynamic effects in cardiomyocyte contractility assays. Each parameter becomes a profiling characteristics of the concentration effect. It can be applied to estimate concentration and compounds effects with an optimal accuracy and could be extended directly to multielectrode array and optical sensing responses

Comparison of compression solutions for impedance and field potential signals of cardiomyocytes

Présentation PosterInternational audienceObjectives. To accurately identify potentially torsadogenic compounds in an earlier stage of drug development, innovative preclinical strategies including label-free impedance and extracellular field potential recordings of stem cell-derived cardiomyocytes have been recently proposed. Unfortunately, they pro-duce high-content signals and size of their data files may exceed 10GB, which prevents any web data transfer for remote data analysis. Therefore, our objec-tive is to compare the performances of several compression algorithms applied to those signals.Methods. The general plan of a lossy compression algorithm consists of three main stages. The first one transforms the signal in a mathematical space where the signal is sparser in order to decorrelate the data and to minimize their amount (one can use for example Discrete Cosine or Fourier Transforms). The se-cond step is the only lossy step of the compression chain. The quantization of the transform coefficients, which can be associated to thresholding discards the non significant coefficients. The last step optimally encodes the quantized coefficients by using an entropy code (e.g. Huffman algorithm, RLE, arithmetic coding…) to exploit residual redundancies of the quantized data. Several combinations of methods mentioned above have been tested and evaluated on two types of one-dimensional signals obtained from impedimetric contractility and extra cellular potential recordings from cardiac myocytes.Results. Results clearly present the ability and reliability of the different methods to compress sensitive data coming from cardiomyocytes with a compression ratio of up to 10:1 while preserving the relevant information content of the recorded data.Conclusion. The proposed method enables biologists to use web-based remote analysis tools for generated cardiomyocyte impedance and field potential data by reducing the size of their files without distortion of their data

Frequency-Dependent Multi-Well Cardiotoxicity Screening Enabled by Optogenetic Stimulation

Side effects on cardiac ion channels causing lethal arrhythmias are one major reason for drug withdrawals from the market. Field potential (FP) recording from cardiomyocytes, is a well-suited tool to assess such cardiotoxic effects of drug candidates in preclinical drug development, but it is currently limited to the spontaneous beating of the cardiomyocytes and manual analysis. Herein, we present a novel optogenetic cardiotoxicity screening system suited for the parallel automated frequency-dependent analysis of drug effects on FP recorded from human-induced pluripotent stem cell-derived cardiomyocytes. For the expression of the light-sensitive cation channel Channelrhodopsin-2, we optimised protocols using virus transduction or transient mRNA transfection. Optical stimulation was performed with a new light-emitting diode lid for a 96-well FP recording system. This enabled reliable pacing at physiologically relevant heart rates and robust recording of FP. Thereby we detected rate-dependent effects of drugs on Na+, Ca2+ and K+ channel function indicated by FP prolongation, FP shortening and the slowing of the FP downstroke component, as well as generation of afterdepolarisations. Taken together, we present a scalable approach for preclinical frequency-dependent screening of drug effects on cardiac electrophysiology. Importantly, we show that the recording and analysis can be fully automated and the technology is readily available using commercial products