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

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

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 fluorescence lifetime imaging microscopy (FLIM) to study metabolism and oxidative stress in biological systems

Study of cellular metabolism and its influence on physiological functions and pathology along with investigation of oxidative stress in pathogenesis are essential for fundamental biology as well as biomedical research. Optical imaging offers the opportunity to assess these indices non-invasively. In this work we apply two-photon fluorescence lifetime imaging microscopy (FLIM) of intrinsic fluorophores for label-free metabolic and oxidative stress imaging in a wide range of biological samples. Analysis of FLIM data was performed by applying the ‘fit-free’ phasor approach where each pixel of the image is transformed to its corresponding phasor on the phasor plot. Biological systems are a rich resource of autofluorescent biomolecules. Their fluorescence lifetimes are sensitive to alteration of normal physiology, making them attractive endogenous probes. We discovered one such endogenous fluorophore with characteristic long fluorescent lifetime. We hypothesized these long lifetime species (LLS) to be fluorescent products of lipid oxidation by reactive oxygen species (ROS), rendering them biomarkers of oxidative stress. To correlate the long lifetime species (LLS) with lipid droplets, we performed simultaneous FLIM and two coherent nonlinear microscopy techniques: third harmonic generation (THG) imaging microscopy and coherent anti-Stokes Raman scattering (CARS) microscopy that are sensitive to lipids. We went one step further to characterize the chemical nature of this discovered species by classical Raman spectral analysis. We show application of this technique in cancer, induced pluripotent stem cell derived cardiomyocytes, as well as in freshly excised mice adipose tissue. The identified endogenous biomarker unfolds opportunities of performing non-invasive measurements of oxidative stress in vivo.We also exploited the autofluorescent coenzyme reduced nicotinamide adenine dinucleotide (NADH), an endogenous probe extensively used for metabolic imaging. We performed NADH-FLIM to study the metabolic status of a vascularized three-dimensional tumor microenvironment in a microfluidic based platform. We could identify metabolically dissimilar regions, as well as identify metabolic response to anticancer drug.Finally, we explored NADH-FLIM of a different class of organisms – bacteria. We show for the first time, FLIM-phasor fingerprint of clinically important bacteria. We discovered interesting bacterial phasor trajectories at different growth phases as well as response to antibiotics, all at single cell resolution

Label-free fluorescence lifetime imaging microscopy (FLIM) to study metabolism and oxidative stress in biological systems

Study of cellular metabolism and its influence on physiological functions and pathology along with investigation of oxidative stress in pathogenesis are essential for fundamental biology as well as biomedical research. Optical imaging offers the opportunity to assess these indices non-invasively. In this work we apply two-photon fluorescence lifetime imaging microscopy (FLIM) of intrinsic fluorophores for label-free metabolic and oxidative stress imaging in a wide range of biological samples. Analysis of FLIM data was performed by applying the ‘fit-free’ phasor approach where each pixel of the image is transformed to its corresponding phasor on the phasor plot. Biological systems are a rich resource of autofluorescent biomolecules. Their fluorescence lifetimes are sensitive to alteration of normal physiology, making them attractive endogenous probes. We discovered one such endogenous fluorophore with characteristic long fluorescent lifetime. We hypothesized these long lifetime species (LLS) to be fluorescent products of lipid oxidation by reactive oxygen species (ROS), rendering them biomarkers of oxidative stress. To correlate the long lifetime species (LLS) with lipid droplets, we performed simultaneous FLIM and two coherent nonlinear microscopy techniques: third harmonic generation (THG) imaging microscopy and coherent anti-Stokes Raman scattering (CARS) microscopy that are sensitive to lipids. We went one step further to characterize the chemical nature of this discovered species by classical Raman spectral analysis. We show application of this technique in cancer, induced pluripotent stem cell derived cardiomyocytes, as well as in freshly excised mice adipose tissue. The identified endogenous biomarker unfolds opportunities of performing non-invasive measurements of oxidative stress in vivo.We also exploited the autofluorescent coenzyme reduced nicotinamide adenine dinucleotide (NADH), an endogenous probe extensively used for metabolic imaging. We performed NADH-FLIM to study the metabolic status of a vascularized three-dimensional tumor microenvironment in a microfluidic based platform. We could identify metabolically dissimilar regions, as well as identify metabolic response to anticancer drug.Finally, we explored NADH-FLIM of a different class of organisms – bacteria. We show for the first time, FLIM-phasor fingerprint of clinically important bacteria. We discovered interesting bacterial phasor trajectories at different growth phases as well as response to antibiotics, all at single cell resolution

Fluorescence lifetime imaging of endogenous biomarker of oxidative stress.

Presence of reactive oxygen species (ROS) in excess of normal physiological level results in oxidative stress. This can lead to a range of pathological conditions including inflammation, diabetes mellitus, cancer, cardiovascular and neurodegenerative disease. Biomarkers of oxidative stress play an important role in understanding the pathogenesis and treatment of these diseases. A number of fluorescent biomarkers exist. However, a non-invasive and label-free identification technique would be advantageous for in vivo measurements. In this work we establish a spectroscopic method to identify oxidative stress in cells and tissues by fluorescence lifetime imaging (FLIM). We identified an autofluorescent, endogenous species with a characteristic fluorescent lifetime distribution as a probe for oxidative stress. To corroborate our hypothesis that these species are products of lipid oxidation by ROS, we correlate the spectroscopic signals arising from lipid droplets by combining FLIM with THG and CARS microscopy which are established techniques for selective lipid body imaging. Further, we performed spontaneous Raman spectral analysis at single points of the sample which provided molecular vibration information characteristics of lipid droplets

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

Metabolic fingerprinting of bacteria by fluorescence lifetime imaging microscopy.

Bacterial populations exhibit a range of metabolic states influenced by their environment, intra- and interspecies interactions. The identification of bacterial metabolic states and transitions between them in their native environment promises to elucidate community behavior and stochastic processes, such as antibiotic resistance acquisition. In this work, we employ two-photon fluorescence lifetime imaging microscopy (FLIM) to create a metabolic fingerprint of individual bacteria and populations. FLIM of autofluorescent reduced nicotinamide adenine dinucleotide (phosphate), NAD(P)H, has been previously exploited for label-free metabolic imaging of mammalian cells. However, NAD(P)H FLIM has not been established as a metabolic proxy in bacteria. Applying the phasor approach, we create FLIM-phasor maps of Escherichia coli, Salmonella enterica serovar Typhimurium, Pseudomonas aeruginosa, Bacillus subtilis, and Staphylococcus epidermidis at the single cell and population levels. The bacterial phasor is sensitive to environmental conditions such as antibiotic exposure and growth phase, suggesting that observed shifts in the phasor are representative of metabolic changes within the cells. The FLIM-phasor approach represents a powerful, non-invasive imaging technique to study bacterial metabolism in situ and could provide unique insights into bacterial community behavior, pathology and antibiotic resistance with sub-cellular resolution