Summary Familial hypertrophic cardiomyopathy (HCM) is a prevalent hereditary cardiac disorder linked to arrhythmia and sudden cardiac death. While the causes of HCM have been identified as genetic mutations in the cardiac sarcomere, the pathways by which sarcomeric mutations engender myocyte hypertrophy and electrophysiological abnormalities are not understood. To elucidate the mechanisms underlying HCM development, we generated patient-specific induced pluripotent stem cell cardiomyocytes (iPSC-CMs) from a ten-member family cohort carrying a hereditary HCM missense mutation (Arg663His) in the MYH7 gene. Diseased iPSC-CMs recapitulated numerous aspects of the HCM phenotype including cellular enlargement and contractile arrhythmia at the single-cell level. Calcium (Ca2+) imaging indicated dysregulation of Ca2+ cycling and elevation in intracellular Ca2+ ([Ca2+]i) are central mechanisms for disease pathogenesis. Pharmacological restoration of Ca2+ homeostasis prevented development of hypertrophy and electrophysiological irregularities. We anticipate that these findings will help elucidate the mechanisms underlying HCM development and identify novel therapies for the disease.

Background Cardiotoxicity is a leading cause for drug attrition during pharmaceutical development and has resulted in numerous preventable patient deaths. Incidents of adverse cardiac drug reactions are more common in patients with pre-existing heart disease than the general population. Here we generated a library of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) from patients with various hereditary cardiac disorders to model differences in cardiac drug toxicity susceptibility for patients of different genetic backgrounds. Methods and Results Action potential duration (APD) and drug-induced arrhythmia were measured at the single cell level in hiPSC-CMs derived from healthy subjects and patients with hereditary long QT syndrome (LQT), familial hypertrophic cardiomyopathy (HCM), and familial dilated cardiomyopathy (DCM). Disease phenotypes were verified in LQT, HCM, and DCM iPSC-CMs by immunostaining and single cell patch clamp. Human embryonic stem cell-derived cardiomyocytes (hESC-CMs) and the human ether-a-go-go-related gene (hERG) expressing human embryonic kidney (HEK293) cells were used as controls. Single cell PCR confirmed expression of all cardiac ion channels in patient-specific hiPSC-CMs as well as hESC-CMs, but not in HEK293 cells. Disease-specific hiPSC-CMs demonstrated increased susceptibility to known cardiotoxic drugs as measured by APD and quantification of drug-induced arrhythmias such as early after depolarizations (EADs) and delayed after depolarizations (DADs). Conclusions We have recapitulated drug-induced cardiotoxicity profiles for healthy subjects, LQT, HCM, and DCM patients at the single cell level for the first time. Our data indicate that healthy and diseased individuals exhibit different susceptibilities to cardiotoxic drugs and that use of disease-specific hiPSC-CMs may predict adverse drug responses more accurately than standard hERG test or healthy control hiPSC-CM/hESC-CM screening assays.

Highly specific Cas9 nucleases derived from SpCas9 are valuable tools for genome editing, but their wide applications are hampered by a lack of knowledge governing guide RNA (gRNA) activity. Here, we perform a genome-scale screen to measure gRNA activity for two highly specific SpCas9 variants (eSpCas9(1.1) and SpCas9-HF1) and wild-type SpCas9 (WT-SpCas9) in human cells, and obtain indel rates of over 50,000 gRNAs for each nuclease, covering ~20,000 genes. We evaluate the contribution of 1,031 features to gRNA activity and develope models for activity prediction. Our data reveals that a combination of RNN with important biological features outperforms other models for activity prediction. We further demonstrate that our model outperforms other popular gRNA design tools. Finally, we develop an online design tool DeepHF for the three Cas9 nucleases. The database, as well as the designer tool, is freely accessible via a web server, http://www.DeepHF.com/.