Category: Assay Development and Screening
Drug-induced pro-arrhythmic cardiotoxicity represents a major concern for drug discovery, as several blockbuster drugs were removed from the market due to their adverse effects on the cardiovascular system. Utilizing stem cell-derived human cardiomyocytes (CM) and high-content imaging provides an opportunity to overcome the limitations of current cardiotoxicity assays, leading to the increase in assay predictiveness and the decrease in drug development costs.
To better predict drug-induced cardiac arrhythmia, modern cardiotoxicity assays have to include both (a) dynamic cell stimulation technologies capable of generating different CM contraction rhythms, and (b) efficient monitoring/image of CM activity using optical methods.
High-content imaging offers non-invasive monitoring of CM activity at the single-cell resolution. However, in order to detect CM contraction, the majority of image analysis approaches requires a cell segmentation step, which makes the whole process very computer-time consuming and incompatible with demands of fast-paced drug screening assays.
Here we report the results of the development of our novel image-based analysis of the multi-parametric activity of optically stimulated cardiomyocytes.
We use pixel intensity variance over time information from the high-speed transmitted-light greyscale movies to separate active and non-active areas of the image. We track control points by looking for a maximum correlation between points from neighboring frames. Contraction amplitude is calculated as an absolute value of pixel displacement over time and the phase is determined by both maximum amplitude and resting state information.
Our initial task was to robustly detect the contraction frequencies only, but during the algorithm development, we realized the need for more information: contraction force and propagation. We applied fluctuation analysis to get this information without the need for manual cell selection or requirement for cell segmentation.
As a result, we receive amplitude-phase space-time profile in an automatic way, allowing us to use the in-depth characterization of the contraction events. The optical setup and the software algorithm were specially designed for autonomous operation to provide reliable measurements from large-scale screens.
We started by validating our image analysis software using bright-field microscopy. The “label-free” nature of our approach is highly advantageous as it allows monitoring cells non-invasively, repeatedly, and over long prolong time without any signal deterioration. Specifically, we were able to automatically detect spontaneous and light-induced contractions of CMs on graphene-based optoelectronic substrates both in control and in the presence of use-dependent drugs.
Further, we proceeded with using our image analysis software using fluorescent microscopy. Kinetic movies of contracting CMs labeled with voltage-sensitive fluorescent dyes were successfully analyzed to extract multi-parametric information about changes in electrical and contractile activities of optically stimulated CMs.
In summary, our novel image-based analysis in combination with dynamic optical stimulation would allow to greatly improve in vitro assessment of drug-induced cardiotoxicity of new drugs.
Volodymyr Cherkas– Postdoctoral Fellow, Bogomoletz Institute of Physiology, Hannover Medical School, Kyiv, Kyyiv, Ukraine
Bogomoletz Institute of Physiology, Hannover Medical School
Kyiv, Kyyiv, Ukraine
A scientist with strong background in Advanced Imaging and Electrophysiology. Extensive expertise in real-time protein tracking, optogenetics, spectroscopy and electrophysiological applications. Expert in optical microscopy hardware and applications. Broad scientific knowledge of cell and molecular biology.