Rupsa Datta

3D microtumors in vitro supported by perfused vascular networks.

There is a growing interest in developing microphysiological systems that can be used to model both normal and pathological human organs in vitro. This “organs-on-chips” approach aims to capture key structural and physiological characteristics of the target tissue. Here we describe in vitro vascularized microtumors (VMTs). This “tumor-on-a-chip” platform incorporates human tumor and stromal cells that grow in a 3D extracellular matrix and that depend for survival on nutrient delivery through living, perfused microvessels. Both colorectal and breast cancer cells grow vigorously in the platform and respond to standard-of-care therapies, showing reduced growth and/or regression. Vascular-targeting agents with different mechanisms of action can also be distinguished, and we find that drugs targeting only VEGFRs (Apatinib and Vandetanib) are not effective, whereas drugs that target VEGFRs, PDGFR and Tie2 (Linifanib and Cabozantinib) do regress the vasculature. Tumors in the VMT show strong metabolic heterogeneity when imaged using NADH Fluorescent Lifetime Imaging Microscopy and, compared to their surrounding stroma, many show a higher free/bound NADH ratio consistent with their known preference for aerobic glycolysis. The VMT platform provides a unique model for studying vascularized solid tumors in vitro.

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.

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 identification of macrophage phenotype by fluorescence lifetime imaging microscopy

Abstract. Macrophages adopt a variety of phenotypes that are a reflection of the many functions they perform as part of the immune system. In particular, metabolism is a phenotypic trait that differs between classically activated, proinflammatory macrophages, and alternatively activated, prohealing macrophages. Inflammatory macrophages have a metabolism based on glycolysis while alternatively activated macrophages generally rely on oxidative phosphorylation to generate chemical energy. We employ this shift in metabolism as an endogenous marker to identify the phenotype of individual macrophages via live-cell fluorescence lifetime imaging microscopy (FLIM). We demonstrate that polarized macrophages can be readily discriminated with the aid of a phasor approach to FLIM, which provides a fast and model-free method for analyzing fluorescence lifetime images.

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.

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 10min after drug administration.

Fluorescence Lifetime Imaging Microscopy to study Metabolism in a Microfluidic Device based Tumor Microenvironment

Here we present 2-photon fluorescence lifetime imaging microscopy of nicotinamide adenine dinucleotide to study metabolism of vascularized “tumor-on-a-chip” consisting of tumor cells, fibroblast and vascular network in an optically clear PDMS device.

Label - free fluorescence lifetime imaging of microfluidic device based three-dimensional cardiac tissue metabolism

In this work, we show mapping of metabolic activity and non-invasive monitoring of drug response of a microphysiological tissue system in a PDMS microfluidic device chamber by fluorescence lifetime imaging of NADH, an endogenous fluorophore