67 research outputs found
Supervised Machine Learning for Classification of the Electrophysiological Effects of Chronotropic Drugs on Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes
Supervised machine learning can be used to predict which drugs human cardiomyocytes have been exposed to. Using electrophysiological data collected from human cardiomyocytes with known exposure to different drugs, a supervised machine learning algorithm can be trained to recognize and classify cells that have been exposed to an unknown drug. Furthermore, the learning algorithm provides information on the relative contribution of each data parameter to the overall classification. Probabilities and confidence in the accuracy of each classification may also be determined by the algorithm. In this study, the electrophysiological effects of β–adrenergic drugs, propranolol and isoproterenol, on cardiomyocytes derived from human induced pluripotent stem cells (hiPS-CM) were assessed. The electrophysiological data were collected using high temporal resolution 2-photon microscopy of voltage sensitive dyes as a reporter of membrane voltage. The results demonstrate the ability of our algorithm to accurately assess, classify, and predict hiPS-CM membrane depolarization following exposure to chronotropic drugs
Automated Detection and Analysis of Depolarization Events in Human Cardiomyocytes using MaDEC
Optical imaging-based methods for assessing the membrane electrophysiology of in vitro human cardiac cells allow for non-invasive temporal assessment of the effect of drugs and other stimuli. Automated methods for detecting and analyzing the depolarization events (DEs) in image-based data allow quantitative assessment of these different treatments. In this study, we use 2-photon microscopy of fluorescent voltage-sensitive dyes (VSDs) to capture the membrane voltage of actively beating human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs). We built a custom and freely available Matlab software, called MaDEC, to detect, quantify, and compare DEs of hiPS-CMs treated with the β-adrenergic drugs, propranolol and isoproterenol. The efficacy of our software is quantified by comparing detection results against manual DE detection by expert analysts, and comparing DE analysis results to known drug-induced electrophysiological effects. The software accurately detected DEs with true positive rates of 98–100% and false positive rates of 1–2%, at signal-to-noise ratios (SNRs) of 5 and above. The MaDEC software was also able to distinguish control DEs from drug-treated DEs both immediately as well as 10 min after drug administration
Label-free Imaging of Metabolism and Oxidative Stress in Human Induced Pluripotent Stem Cell-derived Cardiomyocytes
In this work we demonstrate a label-free optical imaging technique to assess metabolic status and oxidative stress in human induced pluripotent stem cell-derived cardiomyocytes by two-photon fluorescence lifetime imaging of endogenous fluorophores. Our results show the sensitivity of this method to detect shifts in metabolism and oxidative stress in the cardiomyocytes upon pathological stimuli of hypoxia and cardiotoxic drugs. This non-invasive imaging technique could prove beneficial for drug development and screening, especially for in vitro cardiac models created from stem cell-derived cardiomyocytes and to study the pathogenesis of cardiac diseases and therapy
A strategy for integrating essential three-dimensional microphysiological systems of human organs for realistic anticancer drug screening
Cancer is one of the leading causes of morbidity and mortality around the world. Despite some success, traditional anticancer drugs developed to reduce tumor growth face important limitations primarily due to undesirable bone marrow and cardiovascular toxicity. Many drugs fail in clinical development after showing promise in preclinical trials, suggesting that the available in vitro and animal models are poor predictors of drug efficacy and toxicity in humans. Thus, novel models that more accurately mimic the biology of human organs are necessary for high-throughput drug screening. Three-dimensional (3D) microphysiological systems can utilize induced pluripotent stem cell technology, tissue engineering, and microfabrication techniques to develop tissue models of human tumors, cardiac muscle, and bone marrow on the order of 1 mm3 in size. A functional network of human capillaries and microvessels to overcome diffusion limitations in nutrient delivery and waste removal can also nourish the 3D microphysiological tissues. Importantly, the 3D microphysiological tissues are grown on optically clear platforms that offer non-invasive and non-destructive image acquisition with subcellular resolution in real time. Such systems offer a new paradigm for high-throughput drug screening and will significantly improve the efficiency of identifying new drugs for cancer treatment that minimize cardiac and bone marrow toxicity
Slowing the onset of hypoxia increases colony forming efficiency of connective tissue progenitor cells \u3ci\u3ein vitro\u3c/i\u3e
Background: Survival and colony formation by transplanted tissue derived connective tissue progenitor cells (CTPs) are thought to be important factors in the success of clinical tissue engineering strategies for bone regeneration. Transplantation of cells into defects larger than a few millimeters expose cells to a profoundly hypoxic environment. This study tested the hypothesis that delaying the onset of hypoxia will improve the survival and performance of CTPs in vitro.
Methods: To mimic declines seen in an avascular in vivo bone defect, colony forming efficiency by marrow derived nucleated cells was assessed under osteogenic conditions. Variation in the rate of oxygen decline from an oxygen tension of 21% to 0.1% oxygen was explored using an incubator with programmable active control of gas concentrations. The effect of doping cultures with defined concentrations of RBCs was also used to evaluate the potential for RBCs to serve as a natural buffer in the setting of declining oxygen levels.
Results: A delay in onset of hypoxia over 96 hours resulted in a 3-fold increase in the relative colony forming efficiency (rCFE) of CTPs as compared to an immediate onset of hypoxia. The presence of RBCs in vitro inhibited the rCFE of CTPs. Given the negative effects of RBCs, methods of RBC removal were evaluated and compared for their effectiveness of RBC removal and retention of colony forming efficiency.
Conclusions: These data suggest that conditions of hypoxia compromise colony forming efficiency in marrow derived CTPs. However, slowing the rate of decline of oxygen preserved colony forming efficiency at levels achieved in a stable normoxic (3% O2) environment. These data also suggest that RBCs are detrimental to the rCFE of CTPs and that buffy coat is an effective and preferred method for removing RBCs from marrow aspirates while preserving CTPs. These findings may inform clinical strategies for CTP transplantation
Quantifying proliferative and surface marker heterogeneity in colony‐founding connective tissue progenitors and their progeny using time‐lapse microscopy
Connective tissue progenitors (CTPs) are defined as the heterogeneous population of tissue‐resident stem and progenitor cells that are capable of proliferating and differentiating into connective tissue phenotypes. The prevalence and variation in clonal progeny of CTPs can be characterized using a colony formation assay. However, colony assays do not directly assess the characteristics of the colony‐founding CTP. We performed large, field‐of‐view, time‐lapse microscopy to manually track colonies back to the founding cells. Image processing and analysis was used to characterize the colonies and their founding cells. We found that the traditional colony‐forming unit (CFU) assay underestimates the number of founding cells as colonies can be formed by more than one founding cell. After 6 days in culture, colonies do not completely express CD73, CD90, and CD105. Heterogeneity in colony cells was characterized by two cell populations, proliferative and spread cells. Regression modelling of duration of lag phase and doubling time by cell marker suggests the presence of CD90 and CD105 in CTP subpopulations with different proliferative capabilities. From mathematical modelling of clonal colonies, we quantitatively characterized proliferation, migration, and cell marker expression rates to identify desirable clones for selection. Direct assessment of colony formation parameters led to more accurate assessment of CFU heterogeneity. Furthermore, these parameters can be used to quantify the diversity and hierarchy of stem and progenitor cells from a cell source or tissue for tissue engineering applications
Modeling and experimental methods to predict oxygen distribution in bone defects following cell transplantation
We have developed a mathematical model that allows simulation of oxygen distribution in a bone defect as a tool to explore the likely effects of local changes in cell concentration, defect size or geometry, local oxygen delivery with oxygen-generating biomaterials (OGBs), and changes in the rate of oxygen consumption by cells within a defect. Experimental data for the oxygen release rate from an OGB and the oxygen consumption rate of a transplanted cell population are incorporated into the model. With these data, model simulations allow prediction of spatiotemporal oxygen concentration within a given defect and the sensitivity of oxygen tension to changes in critical variables. This information may help to minimize the number of experiments in animal models that determine the optimal combinations of cells, scaffolds, and OGBs in the design of current and future bone regeneration strategies. Bone marrow-derived nucleated cell data suggest that oxygen consumption is dependent on oxygen concentration. OGB oxygen release is shown to be a time-dependent function that must be measured for accurate simulation. Simulations quantify the dependency of oxygen gradients in an avascular defect on cell concentration, cell oxygen consumption rate, OGB oxygen generation rate, and OGB geometry
Three-Dimensional Adult Cardiac Extracellular Matrix Promotes Maturation of Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes
Pluripotent stem cell-derived cardiomyocytes (CMs) have great potential in the development of new therapies for cardiovascular disease. In particular, human induced pluripotent stem cells (iPSCs) may prove especially advantageous due to their pluripotency, their self-renewal potential, and their ability to create patient-specific cell lines. Unfortunately, pluripotent stem cell-derived CMs are immature, with characteristics more closely resembling fetal CMs than adult CMs, and this immaturity has limited their use in drug screening and cell-based therapies. Extracellular matrix (ECM) influences cellular behavior and maturation, as does the geometry of the environment—twodimensional (2D) versus three-dimensional (3D). We therefore tested the hypothesis that native cardiac ECM and 3D cultures might enhance the maturation of iPSC-derived CMs in vitro. We demonstrate that maturation of iPSCderived CMs was enhanced when cells were seeded into a 3D cardiac ECM scaffold, compared with 2D culture. 3D cardiac ECMpromoted increased expression of calcium-handling genes, Junctin, CaV1.2, NCX1, HCN4, SERCA2a, Triadin, and CASQ2. Consistent with this, we find that iPSC-derived CMs in 3D adult cardiac ECM show increased calcium signaling (amplitude) and kinetics (maximum upstroke and downstroke) compared with cells in 2D. Cells in 3D culture were also more responsive to caffeine, likely reflecting an increased availability of calcium in the sarcoplasmic reticulum. Taken together, these studies provide novel strategies for maturing iPSC-derived CMs that may have applications in drug screening and transplantation therapies to treat heart disease
Label-Free Optical Single-Molecule Micro- and Nanosensors
This is the author accepted manuscript. The final version is available from Wiley via the DOI in this recordLabel-free optical sensor systems have emerged that exhibit extraordinary sensitivity for detecting physical, chemical, and biological entities at the micro/nanoscale. Particularly exciting is the detection and analysis of molecules, on miniature optical devices that have many possible applications in health, environment, and security. These micro- and nanosensors have now reached a sensitivity level that allows for the detection and analysis of even single molecules. Their small size enables an exceedingly high sensitivity, and the application of quantum optical measurement techniques can allow the classical limits of detection to be approached or surpassed. The new class of label-free micro- and nanosensors allows dynamic processes at the single-molecule level to be observed directly with light. By virtue of their small interaction length, these micro- and nanosensors probe light–matter interactions over a dynamic range often inaccessible by other optical techniques. For researchers entering this rapidly advancing field of single-molecule micro- and nanosensors, there is an urgent need for a timely review that covers the most recent developments and that identifies the most exciting opportunities. The focus here is to provide a summary of the recent techniques that have either demonstrated label-free single-molecule detection or claim single-molecule sensitivity.Living Systems Institute, University of Exete
Supervised Machine Learning for Classification of the Electrophysiological Effects of Chronotropic Drugs on Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes.
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