Live Cell Imaging on Single Cell Arrays (LISCA)
Fluorescent reporters provide a time-resolved readout of single cell gene expression after transfection, cellular response in signaling cascades, apoptotic events or stem cell differentiation. Imaging in cell-arrays using scanning time lapse microscopy yields hundreds of single cell trajectories and hence ample statistics for computational data analysis. We developed Live Cell Imaging on Single Cell Arrays (LISCA) to record time courses from individual cells in high throughput via automated image acquisition and processing. Single cell fluorescence time traces help e.g. to unravel gene delivery mechanisms and resolve cellular heterogeneity, a hallmark of complex biological systems dominated by intrinsic fluctuations.
Live-cell Imaging of Single-Cell Arrays (LISCA) - a Versatile Technique to Quantify Cellular Kinetics
Anita Reiser, Daniel Woschée, Simon Maximilian Kempe, Joachim Oskar Rädler
JoVe Journal (169), e62025 (2021), Show article
Live-cell Imaging of Single-Cell Arrays (LISCA) is a versatile method to collect time courses of fluorescence signals from individual cells in high throughput. In general, the acquisition of single-cell time courses from cultured cells is hampered by cell motility and diversity of cell shapes. Adhesive micro-arrays standardize single-cell conditions and facilitate image analysis. LISCA combines single-cell microarrays with scanning time-lapse microscopy and automated image processing. Here, we describe the experimental steps of taking single-cell fluorescence time courses in a LISCA format. We transfect cells adherent to a micropatterned array using mRNA encoding for enhanced green fluorescent protein (eGFP) and monitor the eGFP expression kinetics of hundreds of cells in parallel via scanning time-lapse microscopy. The image data stacks are automatically processed by newly developed software that integrates fluorescence intensity over selected cell contours to generate single-cell fluorescence time courses. We demonstrate that eGFP expression time courses after mRNA transfection are well described by a simple kinetic translation model that reveals expression and degradation rates of mRNA. Further applications of LISCA for event time correlations of multiple markers in the context of signaling apoptosis are discussed.
A High-throughput Microscopy Method for Single-Cell Analysis of Event-time Correlations in Nanoparticle-Induced Cell Death
A. Murschhauser, P. J. F. Röttgermann, D. Woschée, M. F. Ober, Y. Yan, K. A. Dawson, J. O. Rädler
Communications Biology, 2, 35, (2019), Show article
The temporal context of cell death decisions remains generally hidden in ensemble mea- surements with endpoint readouts. Here, we describe a method to extract event times from fluorescence time traces of cell death-related markers in automated live-cell imaging on single-cell arrays (LISCA) using epithelial A549 lung and Huh7 liver cancer cells as a model system. In pairwise marker combinations, we assess the chronological sequence and delay times of the events lysosomal membrane permeabilization, mitochondrial outer membrane permeabilization and oxidative burst after exposure to 58 nm amino-functionalized poly- styrene nanoparticles (PS-NH2 nanoparticles). From two-dimensional event-time scatter plots we infer a lysosomal signal pathway at a low dose of nanoparticles (25 µgmL−1) for both cell lines, while at a higher dose (100 µgmL−1) a mitochondrial pathway coexists in A549 cells, but not in Huh7. In general, event-time correlations provide detailed insights into heterogeneity and interdependencies in signal transmission pathways.
S. Westermayer, J. Mergerle, G. Fritz, U. Gerland & J. O. Rädler
Bacteria can rapidly react to environmental changes by adapting gene expression of certain genes. We investigate the time-dependent response of sugar utilization systems in Escherichia coli on the single-cell level. We study both individual systems and the situation of two competing sugar utilization systems, with the goal to characterize properties that may have been optimized by evolution. Using microfluidic set-ups we expose bacterial cultures to systematically variable environments and use time-lapse microscopy and single cell tracking to acquire single-cell expression kinetics. In mathematical models using cost-benefit analysis and game theoretical concepts, we compare different regulatory schemes as strategies to cope with variable environments.
This work is supported by the DFG through the priority program SPP
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