All-Optical Electrophysiology Refines Populations of In Silico Human iPSC-CMs for Drug Evaluation
All-Optical Electrophysiology Refines Populations of In Silico Human iPSC-CMs for Drug Evaluation
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DOI：
10.1016/j.bpj.2020.03.018
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发表时间：
2020-05-19
影响因子：
3.4
通讯作者：
Entcheva, Emilia
中科院分区：
文献类型：
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作者：
Paci, Michelangelo;Passini, Elisa;Entcheva, Emilia
高通量体外药物测定受到人类诱导多能干细胞衍生心肌细胞（hiPSC-CM）技术的最新进展以及同时测量动作电位（AP）和Ca 2+瞬变（CaTrs）的非接触式全光学系统的影响。并行计算的进步表明，计算机模拟可以高精度地预测药物作用。我们结合联合收割机这些体外和计算机技术，并证明了高通量实验数据的实用性，以完善计算机hiPSC-CM群体，并预测和解释药物作用机制。使用光学获得的hiPSC-CM AP和CaTrs，这些AP和CaTrs来自自发活动，并且在对照和药物条件下在光学起搏下以多个剂量使用。开发了一个更新版本的2018年模型，以完善hiPSC-CM自发电活动的描述;使用同时记录的AP和CaTrs构建并校准了一个计算机模拟hiPSC-CM群体。我们在计算机上测试了五种药物（阿司咪唑，多非利特，伊布利特，苄普地尔和地尔硫卓），并将结果与体外光学记录进行比较。我们的模拟表明，生理上准确的人口模型可以通过整合AP和CaTr控制记录。因此，构建的模型群体正确预测了药物效应和不良事件的发生，即使群体仅基于对照数据进行了优化，并且在其校准期间未部署体外药物测试数据。此外，计算机模拟研究产生了机械见解;例如，通过模拟，与hiPSC-CM相比，苄普地尔在成年心肌细胞中更具有促炎作用，这可以追溯到两者中离子电流的不同表达。因此，我们的工作1）支持全光学电生理学在提供高内容数据以改进实验校准的计算机模拟hiPSC-CM群体方面的效用，2）在将hiPSC-CM中获得的结果转化为人类时，提供了对某些限制的见解，和3）显示了高通量体外和计算机模拟方法相结合的优势。意义我们证明了人类计算机模拟药物的整合试验和光学记录的来自人诱导多能干细胞衍生的心肌细胞（hiPSCCM）的合胞体的同时动作电位和钙瞬变数据，用于药物作用的预测和机制研究。我们提出了一个计算机模拟模型群体，1）基于新的hiPSC-CM模型，概括了hiPSC-CM自动性的机制，2）使用全视测量进行校准。我们使用我们的计算机人口来预测和评估五种药物的作用和潜在的生物物理机制，获得与我们的实验和一个独立数据集一致的结果。这项工作支持结合使用高内容，高质量的全光学电生理学数据和计算机模拟hiPSC-CM来进行，增强和解释药物试验。
High-throughput in vitro drug assays have been impacted by recent advances in human induced pluripotent stem cell-derived cardiomyocyte (hiPSC-CM) technology and by contact-free all-optical systems simultaneously measuring action potentials (APs) and Ca2+ transients (CaTrs). Parallel computational advances have shown that in silico simulations can predict drug effects with high accuracy. We combine these in vitro and in silico technologies and demonstrate the utility of highthroughput experimental data to refine in silico hiPSC-CM populations and to predict and explain drug action mechanisms. Optically obtained hiPSC-CM APs and CaTrs were used from spontaneous activity and under optical pacing in control and drug conditions at multiple doses. An updated version of the Paci2018 model was developed to refine the description of hiPSC-CM spontaneous electrical activity; a population of in silico hiPSC-CMs was constructed and calibrated using simultaneously recorded APs and CaTrs. We tested in silico five drugs (astemizole, dofetilide, ibutilide, bepridil, and diltiazem) and compared the outcomes to in vitro optical recordings. Our simulations showed that physiologically accurate population of models can be obtained by integrating AP and CaTr control records. Thus, constructed population of models correctly predicted the drug effects and occurrence of adverse episodes, even though the population was optimized only based on control data and in vitro drug testing data were not deployed during its calibration. Furthermore, the in silico investigation yielded mechanistic insights; e.g., through simulations, bepridil's more proarrhythmic action in adult cardiomyocytes compared to hiPSC-CMs could be traced to the different expression of ion currents in the two. Therefore, our work 1) supports the utility of all-optical electrophysiology in providing high-content data to refine experimentally calibrated populations of in silico hiPSC-CMs, 2) offers insights into certain limitations when translating results obtained in hiPSC-CMs to humans, and 3) shows the strength of combining highthroughput in vitro and population in silico approaches.SIGNIFICANCE We demonstrate the integration of human in silico drug trials and optically recorded simultaneous action potential and calcium transient data from syncytia of human induced pluripotent stem cell-derived cardiomyocytes (hiPSCCMs) for prediction and mechanistic investigations of drug action. We propose a population of in silico models 1) based on a new hiPSC-CM model recapitulating the mechanisms underlying hiPSC-CM automaticity and 2) calibrated with alloptical measurements. We used our in silico population to predict and evaluate the effects of five drugs and the underlying biophysical mechanisms, obtaining results in agreement with our experiments and one independent data set. This work supports the combined use of high-content, high-quality all-optical electrophysiology data and in silico hiPSC-CM simulations to conduct, augment, and interpret drug trials.