Unlocking Medical Discoveries

The development of cardiomyopathies, a leading cause of heart failure, has been strongly linked to dysregulated calcium handling in cardiomyocytes. In healthy cardiac cells, the process of synchronized contraction is regulated by excitation-contraction coupling, a mechanism that ensures precise calcium signaling and myofilament activation. However, under disease conditions—human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) often exhibit: 1) dysfunctional calcium homeostasis and 2) impaired contractility, critical for cardiac function. This study used a novel myofilament-localized optical biosensor, RGECO-TnT, which allows the analysis of calcium transients in hiPSC-CMs from diagnosed DCM patients and a healthy control, revealing key disease phenotypes and interesting insights for cardiovascular drug developers. Our study identified distinct differences in calcium handling between the DCM patients and healthy controls at the single cell level, suggesting patient-specific calcium handling signatures. We provide a robust framework for investigating calcium transients and sarcomeric organization. By integrating optical biosensor technology into preclinical pipelines, we can help de-risk therapeutic strategies by evaluating specific drug-responses with unprecedented precision.

Genetically encoded biosensors, combined with high-content FRET imaging, have the potential to transform tracking of cellular signalling events by enabling single-cell analysis of dynamic cellular responses to drugs. Such analysis increases the power of traditional "homogeneity assumptions" in bulk measurements, revealing cellular heterogeneity within seemingly uniform populations. In this study, we explored the interactions between protein kinase A (PKA) and extracellular signal-regulated kinase 1/2 (ERK1/2) signaling pathways in striatal neurons, revealing novel crosstalk mechanisms and drug-induced pathway activation. FRET-based biosensors helped us to identify distinct drug responsiveness patterns in neuronal subpopulations, categorized as low, medium, or high responders based on nuclear morphology. Technical advances in single-cell profiling have led to an evolving understanding of cell-type heterogeneity in signaling dynamics and drug responses. This case study highlights the variability in how cells respond to pharmacological stimuli, emphasizing the need for single-cell analysis to capture these subtle effects. Ultimately, our platform provides interesting insights in drug discovery hit-to-lead stages by capturing the variability in response magnitude and kinetics across individual cells. The biosensors are powerful tools for understanding complex signaling networks and drug effects, ultimately supporting more precise neuropharmacology drug discovery efforts.

For years, cardiovascular research faced significant challenges due to limited accessibility to human cardiomyocytes. Because of this limitation, researchers relied on rodent models to study cardiac function and associated pathophysiology. Although these models offer valuable insights, there are persistent translational challenges due to interspecies differences. A paradigm shift was the emergence of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), offering scalable and patient-specific models for studying human cardiac biology. To highlight their relevance, we compared activation of distinct signaling pathways as well as transcriptomic profiles of hiPSC-CMs with neonatal rat primary cardiomyocytes (RNCMs). Using biosensors, we explored GPCR-mediated nuclear protein kinase A (PKA) and extracellular signal-regulated kinase (ERK1/2) activities in both models. RNCMs and hiPSC-CMs demonstrated distinct signaling behaviors, reflecting species-specific signal transduction processes, which need to be considered in human drug discovery. Another advantage derived from hiPSC-CMs is the reduced need for overexpression systems such as in HEK 293 cells in drug discovery programs. By leveraging the combination of hiPSCs and biosensors, we aim to pave the way for more accurate and predictive models in cardiovascular research and drug development.