Image-based evaluation of contraction–relaxation kinetics of human-induced pluripotent stem cell-derived cardiomyocytes: Correlation and complementarity with extracellular electrophysiology

AbstractIn this study, we used high-speed video microscopy with motion vector analysis to investigate the contractile characteristics of hiPS-CM monolayer, in addition to further characterizing the motion with extracellular field potential (FP), traction force and the Ca2+ transient. Results of our traction force microscopy demonstrated that the force development of hiPS-CMs correlated well with the cellular deformation detected by the video microscopy with motion vector analysis. In the presence of verapamil and isoproterenol, contractile motion of hiPS-CMs showed alteration in accordance with the changes in fluorescence peak of the Ca2+ transient, i.e., upstroke, decay, amplitude and full-width at half-maximum. Simultaneously recorded hiPS-CM motion and FP showed that there was a linear correlation between changes in the motion and field potential duration in response to verapamil (30–150nM), isoproterenol (0.1–10μM) and E-4031 (10–50nM). In addition, tetrodotoxin (3–30μM)-induced delay of sodium current was corresponded with the delay of the contraction onset of hiPS-CMs. These results indicate that the electrophysiological and functional behaviors of hiPS-CMs are quantitatively reflected in the contractile motion detected by this image-based technique. In the presence of 100nM E-4031, the occurrence of early after-depolarization-like negative deflection in FP was also detected in the hiPS-CM motion as a characteristic two-step relaxation pattern. These findings offer insights into the interpretation of the motion kinetics of the hiPS-CMs, and are relevant for understanding electrical and mechanical relationship in hiPS-CMs

A deep learning algorithm to translate and classify cardiac electrophysiology

The development of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) has been a critical in vitro advance in the study of patient-specific physiology, pathophysiology, and pharmacology. We designed a new deep learning multitask network approach intended to address the low throughput, high variability, and immature phenotype of the iPSC-CM platform. The rationale for combining translation and classification tasks is because the most likely application of the deep learning technology we describe here is to translate iPSC-CMs following application of a perturbation. The deep learning network was trained using simulated action potential (AP) data and applied to classify cells into the drug-free and drugged categories and to predict the impact of electrophysiological perturbation across the continuum of aging from the immature iPSC-CMs to the adult ventricular myocytes. The phase of the AP extremely sensitive to perturbation due to a steep rise of the membrane resistance was found to contain the key information required for successful network multitasking. We also demonstrated successful translation of both experimental and simulated iPSC-CM AP data validating our network by prediction of experimental drug-induced effects on adult cardiomyocyte APs by the latter

Improvement of acquisition and analysis methods in multi-electrode array experiments with iPS cell-derived cardiomyocytes

AbstractIntroductionMulti-electrode array (MEA) systems and human induced pluripotent stem (iPS) cell-derived cardiomyocytes are frequently used to characterize the electrophysiological effects of drug candidates for the prediction of QT prolongation and proarrhythmic potential. However, the optimal experimental conditions for obtaining reliable experimental data, such as high-pass filter (HPF) frequency and cell plating density, remain to be determined.MethodsExtracellular field potentials (FPs) were recorded from iPS cell-derived cardiomyocyte sheets by using the MED64 and MEA2100 multi-electrode array systems. Effects of HPF frequency (0.1 or 1Hz) on FP duration (FPD) were assessed in the presence and absence of moxifloxacin, terfenadine, and aspirin. The influence of cell density on FP characteristics recorded through a 0.1-Hz HPF was examined. The relationship between FP and action potential (AP) was elucidated by simultaneous recording of FP and AP using a membrane potential dye.ResultsMany of the FP waveforms recorded through a 1-Hz HPF were markedly deformed and appeared differentiated compared with those recorded through a 0.1-Hz HPF. The concentration–response curves for FPD in the presence of terfenadine reached a steady state at concentrations of 0.1 and 0.3μM when a 0.1-Hz HPF was used. In contrast, FPD decreased at a concentration of 0.3μM with a characteristic bell-shaped concentration–response curve when a 1-Hz HPF was used. The amplitude of the first and second peaks in the FP waveform increased with increasing cell plating density. The second peak of the FP waveform roughly coincided with AP signal at 50% repolarization, and the negative deflection at the second peak of the FP waveform in the presence of E-4031 corresponded to early afterdepolarization and triggered activity.DiscussionFP can be used to assess the QT prolongation and proarrhythmic potential of drug candidates; however, experimental conditions such as HPF frequency are important for obtaining reliable data

Investigation of drugs for the prevention of doxorubicin-induced cardiac events using big data analysis

Aim: Doxorubicin, an anthracycline anti-tumour agent, is an essential chemotherapeutic drug; however, the adverse events associated with doxorubicin usage, including cardiotoxicity, prevent patients from continuing treatment. Here, we used databases to explore existing approved drugs with potential preventative effects against doxorubicin-induced cardiac events and examined their efficacy and mechanisms. Methods: The Gene Expression Omnibus (GEO), Library of Integrated Network-based Cellular Signatures (LINCS), and Food and Drug Administration Adverse Events Reporting System (FAERS) databases were used to extract candidate prophylactic drugs. Mouse models of doxorubicin-induced cardiac events were generated by intraperitoneal administration of 20 mg/kg of doxorubicin on Day 1 and oral administration of prophylactic candidate drugs for 6 consecutive days beginning the day before doxorubicin administration. On Day 6, mouse hearts were extracted and examined for mRNA expression of apoptosis-related genes. Results: GEO analysis showed that doxorubicin administration upregulated 490 genes and downregulated 862 genes, and LINCS data identified sirolimus, verapamil, minoxidil, prednisolone, guanabenz, and mosapride as drugs capable of counteracting these genetic alterations. Examination of the effects of these drugs on cardiac toxicity using FAERS identified sirolimus and mosapride as new prophylactic drug candidates. In model mice, mosapride and sirolimus suppressed the Bax/Bcl-2 mRNA ratio, which is elevated in doxorubicin-induced cardiotoxicity. These drugs also suppressed the expression of inflammatory cytokines Il1b and Il6 and markers associated with myocardial fibrosis, including Lgal3 and Timp1. Conclusion: These findings suggest that doxorubicin-induced cardiac events are suppressed by the administration of mosapride and sirolimus

Highly Sensitive In Vitro Methods for Detection of Residual Undifferentiated Cells in Retinal Pigment Epithelial Cells Derived from Human iPS Cells

Human induced pluripotent stem cells (hiPSCs) possess the capabilities of self-renewal and differentiation into multiple cell types, and they are free of the ethical problems associated with human embryonic stem cells (hESCs). These characteristics make hiPSCs a promising choice for future regenerative medicine research. There are significant obstacles, however, preventing the clinical use of hiPSCs. One of the most obvious safety issues is the presence of residual undifferentiated cells that have tumorigenic potential. To locate residual undifferentiated cells, in vivo teratoma formation assays have been performed with immunodeficient animals, which is both costly and time-consuming. Here, we examined three in vitro assay methods to detect undifferentiated cells (designated an in vitro tumorigenicity assay): soft agar colony formation assay, flow cytometry assay and quantitative real-time polymerase chain reaction assay (qRT-PCR). Although the soft agar colony formation assay was unable to detect hiPSCs even in the presence of a ROCK inhibitor that permits survival of dissociated hiPSCs/hESCs, the flow cytometry assay using anti-TRA-1-60 antibody detected 0.1% undifferentiated hiPSCs that were spiked in primary retinal pigment epithelial (RPE) cells. Moreover, qRT-PCR with a specific probe and primers was found to detect a trace amount of Lin28 mRNA, which is equivalent to that present in a mixture of a single hiPSC and 5.0×104 RPE cells. Our findings provide highly sensitive and quantitative in vitro assays essential for facilitating safety profiling of hiPSC-derived products for future regenerative medicine research

The whole blood transcriptional regulation landscape in 465 COVID-19 infected samples from Japan COVID-19 Task Force

「コロナ制圧タスクフォース」COVID-19患者由来の血液細胞における遺伝子発現の網羅的解析 --重症度に応じた遺伝子発現の変化には、ヒトゲノム配列の個人差が影響する--. 京都大学プレスリリース. 2022-08-23.Coronavirus disease 2019 (COVID-19) is a recently-emerged infectious disease that has caused millions of deaths, where comprehensive understanding of disease mechanisms is still unestablished. In particular, studies of gene expression dynamics and regulation landscape in COVID-19 infected individuals are limited. Here, we report on a thorough analysis of whole blood RNA-seq data from 465 genotyped samples from the Japan COVID-19 Task Force, including 359 severe and 106 non-severe COVID-19 cases. We discover 1169 putative causal expression quantitative trait loci (eQTLs) including 34 possible colocalizations with biobank fine-mapping results of hematopoietic traits in a Japanese population, 1549 putative causal splice QTLs (sQTLs; e.g. two independent sQTLs at TOR1AIP1), as well as biologically interpretable trans-eQTL examples (e.g., REST and STING1), all fine-mapped at single variant resolution. We perform differential gene expression analysis to elucidate 198 genes with increased expression in severe COVID-19 cases and enriched for innate immune-related functions. Finally, we evaluate the limited but non-zero effect of COVID-19 phenotype on eQTL discovery, and highlight the presence of COVID-19 severity-interaction eQTLs (ieQTLs; e.g., CLEC4C and MYBL2). Our study provides a comprehensive catalog of whole blood regulatory variants in Japanese, as well as a reference for transcriptional landscapes in response to COVID-19 infection

DOCK2 is involved in the host genetics and biology of severe COVID-19

「コロナ制圧タスクフォース」COVID-19疾患感受性遺伝子DOCK2の重症化機序を解明 --アジア最大のバイオレポジトリーでCOVID-19の治療標的を発見--. 京都大学プレスリリース. 2022-08-10.Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge. Here we conducted a genome-wide association study (GWAS) involving 2, 393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3, 289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target