Dataset Information

Automated Imaging and Analysis for the Quantification of Fluorescently Labeled Macropinosomes.

ABSTRACT: Macropinocytosis is a non-specific fluid-phase uptake pathway that allows cells to internalize large extracellular cargo, such as proteins, pathogens, and cell debris, through bulk endocytosis. This pathway plays an essential role in a variety of cellular processes, including the regulation of immune responses and cancer cell metabolism. Given this importance in biological function, examining cell culture conditions can provide valuable information by identifying regulators of this pathway and optimizing conditions to be employed in the discovery of novel therapeutic approaches. The study describes an automated imaging and analysis technique using standard laboratory equipment and a cell imaging multi-mode plate reader for the rapid quantification of the macropinocytic index in adherent cells. The automated method is based on the uptake of high molecular weight fluorescent dextran and can be applied to 96-well microplates to facilitate assessments of multiple conditions in one experiment or fixed samples mounted onto glass coverslips. This approach is aimed at maximizing reproducibility and reducing experimental variation while being both time-saving and cost-effective.

SUBMITTER: Galenkamp KMO

PROVIDER: S-EPMC8919987 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

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Publications

Automated Imaging and Analysis for the Quantification of Fluorescently Labeled Macropinosomes.

Galenkamp Koen M O KMO Galapate Cheska Marie CM Zhang Yijuan Y Commisso Cosimo C

Journal of visualized experiments : JoVE 20210824 174

Macropinocytosis is a non-specific fluid-phase uptake pathway that allows cells to internalize large extracellular cargo, such as proteins, pathogens, and cell debris, through bulk endocytosis. This pathway plays an essential role in a variety of cellular processes, including the regulation of immune responses and cancer cell metabolism. Given this importance in biological function, examining cell culture conditions can provide valuable information by identifying regulators of this pathway and o ...[more]

PMID: 34515683

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Project description:Recent advances in imaging technology and fluorescent probes have made it possible to gain information about the dynamics of subcellular processes at unprecedented spatiotemporal scales. Unfortunately, a lack of automated tools to efficiently process the resulting imaging data encoding fine details of the biological processes remains a major bottleneck in utilizing the full potential of these powerful experimental techniques. Here we present a computational tool, called PunctaSpecks, that can characterize fluorescence signals arising from a wide range of biological molecules under normal and pathological conditions. Among other things, the program can calculate the number, areas, life-times, and amplitudes of fluorescence signals arising from multiple sources, track diffusing fluorescence sources like moving mitochondria, and determine the overlap probability of two processes or organelles imaged using indicator dyes of different colors. We have tested PunctaSpecks on synthetic time-lapse movies containing mobile fluorescence objects of various sizes, mimicking the activity of biomolecules. The robustness of the software is tested by varying the level of noise along with random but known pattern of appearing, disappearing, and movement of these objects. Next, we use PunctaSpecks to characterize protein-protein interaction involved in store-operated Ca2+ entry through the formation and activation of plasma membrane-bound ORAI1 channel and endoplasmic reticulum membrane-bound stromal interaction molecule (STIM), the evolution of inositol 1,4,5-trisphosphate (IP3)-induced Ca2+ signals from sub-micrometer size local events into global waves in human cortical neurons, and the activity of Alzheimer's disease-associated β amyloid pores in the plasma membrane. The tool can also be used to study other dynamical processes imaged through fluorescence molecules. The open source algorithm allows for extending the program to analyze more than two types of biomolecules visualized using markers of different colors.

Dataset Information

Automated Imaging and Analysis for the Quantification of Fluorescently Labeled Macropinosomes.

Publications

Automated Imaging and Analysis for the Quantification of Fluorescently Labeled Macropinosomes.

Similar Datasets

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