BeatProfiler: Multimodal In Vitro Analysis of Cardiac Function Enables Machine Learning Classification of Diseases and Drugs.

Goal: Contractile response and calcium handling are central to understanding cardiac function and physiology, yet existing methods of analysis to quantify these metrics are often time-consuming, prone to mistakes, or require specialized equipment/license. We developed BeatProfiler, a suite of cardiac analysis tools designed to quantify contractile function, calcium handling, and force generation for multiple in vitro cardiac models and apply downstream machine learning methods for deep phenotyping and classification. Methods: We first validate BeatProfiler's accuracy, robustness, and speed by benchmarking against existing tools with a fixed dataset. We further confirm its ability to robustly characterize disease and dose-dependent drug response. We then demonstrate that the data acquired by our automatic acquisition pipeline can be further harnessed for machine learning (ML) analysis to phenotype a disease model of restrictive cardiomyopathy and profile cardioactive drug functional response. To accurately classify between these biological signals, we apply feature-based ML and deep learning models (temporal convolutional-bidirectional long short-term memory model or TCN-BiLSTM). Results: Benchmarking against existing tools revealed that BeatProfiler detected and analyzed contraction and calcium signals better than existing tools through improved sensitivity in low signal data, reduction in false positives, and analysis speed increase by 7 to 50-fold. Of signals accurately detected by published methods (PMs), BeatProfiler's extracted features showed high correlations to PMs, confirming that it is reliable and consistent with PMs. The features extracted by BeatProfiler classified restrictive cardiomyopathy cardiomyocytes from isogenic healthy controls with 98% accuracy and identified relax90 as a top distinguishing feature in congruence with previous findings. We also show that our TCN-BiLSTM model was able to classify drug-free control and 4 cardiac drugs with different mechanisms of action at 96% accuracy. We further apply Grad-CAM on our convolution-based models to identify signature regions of perturbations by these drugs in calcium signals. Conclusions: We anticipate that the capabilities of BeatProfiler will help advance in vitro studies in cardiac biology through rapid phenotyping, revealing mechanisms underlying cardiac health and disease, and enabling objective classification of cardiac disease and responses to drugs.

Macrophages enhance contractile force in iPSC-derived human engineered cardiac tissue.

Resident cardiac macrophages are critical mediators of cardiac function. Despite their known importance to cardiac electrophysiology and tissue maintenance, there are currently no stem-cell-derived models of human engineered cardiac tissues (hECTs) that include resident macrophages. In this study, we made an induced pluripotent stem cell (iPSC)-derived hECT model with a resident population of macrophages (iM0) to better recapitulate the native myocardium and characterized their impact on tissue function. Macrophage retention within the hECTs was confirmed via immunofluorescence after 28 days of cultivation. The inclusion of iM0s significantly impacted hECT function, increasing contractile force production. A potential mechanism underlying these changes was revealed by the interrogation of calcium signaling, which demonstrated the modulation of ß-adrenergic signaling in +iM0 hECTs. Collectively, these findings demonstrate that macrophages significantly enhance cardiac function in iPSC-derived hECT models, emphasizing the need to further explore their contributions not only in healthy hECT models but also in the contexts of disease and injury.

Modeling the Effects of Protracted Cosmic Radiation in a Human Organ-on-Chip Platform.

Galactic cosmic radiation (GCR) is one of the most serious risks posed to astronauts during missions to the Moon and Mars. Experimental models capable of recapitulating human physiology are critical to understanding the effects of radiation on human organs and developing radioprotective measures against space travel exposures. The effects of systemic radiation are studied using a multi-organ-on-a-chip (multi-OoC) platform containing engineered tissue models of human bone marrow (site of hematopoiesis and acute radiation damage), cardiac muscle (site of chronic radiation damage) and liver (site of metabolism), linked by vascular circulation with an endothelial barrier separating individual tissue chambers from the vascular perfusate. Following protracted neutron radiation, the most damaging radiation component in deep space, a greater deviation of tissue function is observed as compared to the same cumulative dose delivered acutely. Further, by characterizing engineered bone marrow (eBM)-derived immune cells in circulation, 58 unique genes specific to the effects of protracted neutron dosing are identified, as compared to acutely irradiated and healthy tissues. It propose that this bioengineered platform allows studies of human responses to extended radiation exposure in an "astronaut-on-a-chip" model that can inform measures for mitigating cosmic radiation injury.

An engineered human cardiac tissue model reveals contributions of systemic lupus erythematosus autoantibodies to myocardial injury.

Systemic lupus erythematosus (SLE) is a highly heterogenous autoimmune disease that affects multiple organs, including the heart. The mechanisms by which myocardial injury develops in SLE, however, remain poorly understood. Here we engineered human cardiac tissues and cultured them with IgG fractions containing autoantibodies from SLE patients with and without myocardial involvement. We observed unique binding patterns of IgG from two patient subgroups: (i) patients with severe myocardial inflammation exhibited enhanced binding to apoptotic cells within cardiac tissues subjected to stress, and (ii) patients with systolic dysfunction exhibited enhanced binding to the surfaces of viable cardiomyocytes. Functional assays and RNA sequencing (RNA-seq) revealed that IgGs from patients with systolic dysfunction exerted direct effects on engineered tissues in the absence of immune cells, altering tissue cellular composition, respiration and calcium handling. Autoantibody target characterization by phage immunoprecipitation sequencing (PhIP-seq) confirmed distinctive IgG profiles between patient subgroups. By coupling IgG profiling with cell surface protein analyses, we identified four pathogenic autoantibody candidates that may directly alter the function of cells within the myocardium. Taken together, these observations provide insights into the cellular processes of myocardial injury in SLE that have the potential to improve patient risk stratification and inform the development of novel therapeutic strategies.

An engineered human cardiac tissue model reveals contributions of systemic lupus erythematosus autoantibodies to myocardial injury.

Systemic lupus erythematosus (SLE) is a heterogenous autoimmune disease that affects multiple organs, including the heart. The mechanisms of myocardial injury in SLE remain poorly understood. In this study, we engineered human cardiac tissues and cultured them with IgG from patients with SLE, with and without myocardial involvement. IgG from patients with elevated myocardial inflammation exhibited increased binding to apoptotic cells within cardiac tissues subjected to stress, whereas IgG from patients with systolic dysfunction exhibited enhanced binding to the surface of live cardiomyocytes. Functional assays and RNA sequencing revealed that, in the absence of immune cells, IgG from patients with systolic dysfunction altered cellular composition, respiration and calcium handling. Phage immunoprecipitation sequencing (PhIP-seq) confirmed distinctive IgG profiles between patient subgroups. Coupling IgG profiling with cell surfaceome analysis identified four potential pathogenic autoantibodies that may directly affect the myocardium. Overall, these insights may improve patient risk stratification and inform the development of new therapeutic strategies.

Engineered cardiac tissue model of restrictive cardiomyopathy for drug discovery.

Restrictive cardiomyopathy (RCM) is defined as increased myocardial stiffness and impaired diastolic relaxation leading to elevated ventricular filling pressures. Human variants in filamin C (FLNC) are linked to a variety of cardiomyopathies, and in this study, we investigate an in-frame deletion (c.7416_7418delGAA, p.Glu2472_Asn2473delinAsp) in a patient with RCM. Induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) with this variant display impaired relaxation and reduced calcium kinetics in 2D culture when compared with a CRISPR-Cas9-corrected isogenic control line. Similarly, mutant engineered cardiac tissues (ECTs) demonstrate increased passive tension and impaired relaxation velocity compared with isogenic controls. High-throughput small-molecule screening identifies phosphodiesterase 3 (PDE3) inhibition by trequinsin as a potential therapy to improve cardiomyocyte relaxation in this genotype. Together, these data demonstrate an engineered cardiac tissue model of RCM and establish the translational potential of this precision medicine approach to identify therapeutics targeting myocardial relaxation.