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Nebbioso G, Yosief R, Koshkin V, Qiu Y, Peng C, Elisseev V, Krylov SN. Automated identification and tracking of cells in Cytometry of Reaction Rate Constant (CRRC). PLoS One 2023; 18:e0282990. [PMID: 37399195 DOI: 10.1371/journal.pone.0282990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 02/28/2023] [Indexed: 07/05/2023] Open
Abstract
Cytometry of Reaction Rate Constant (CRRC) is a method for studying cell-population heterogeneity using time-lapse fluorescence microscopy, which allows one to follow reaction kinetics in individual cells. The current and only CRRC workflow utilizes a single fluorescence image to manually identify cell contours which are then used to determine fluorescence intensity of individual cells in the entire time-stack of images. This workflow is only reliable if cells maintain their positions during the time-lapse measurements. If the cells move, the original cell contours become unsuitable for evaluating intracellular fluorescence and the CRRC experiment will be inaccurate. The requirement of invariant cell positions during a prolonged imaging is impossible to satisfy for motile cells. Here we report a CRRC workflow developed to be applicable to motile cells. The new workflow combines fluorescence microscopy with transmitted-light microscopy and utilizes a new automated tool for cell identification and tracking. A transmitted-light image is taken right before every fluorescence image to determine cell contours, and cell contours are tracked through the time-stack of transmitted-light images to account for cell movement. Each unique contour is used to determine fluorescence intensity of cells in the associated fluorescence image. Next, time dependencies of the intracellular fluorescence intensities are used to determine each cell's rate constant and construct a kinetic histogram "number of cells vs rate constant." The new workflow's robustness to cell movement was confirmed experimentally by conducting a CRRC study of cross-membrane transport in motile cells. The new workflow makes CRRC applicable to a wide range of cell types and eliminates the influence of cell motility on the accuracy of results. Additionally, the workflow could potentially monitor kinetics of varying biological processes at the single-cell level for sizable cell populations. Although our workflow was designed ad hoc for CRRC, this cell-segmentation/cell-tracking strategy also represents an entry-level, user-friendly option for a variety of biological assays (i.e., migration, proliferation assays, etc.). Importantly, no prior knowledge of informatics (i.e., training a model for deep learning) is required.
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Affiliation(s)
- Giammarco Nebbioso
- Department of Chemistry, York University, Toronto, Ontario, Canada
- Centre for Research on Biomolecular Interactions, York University, Toronto, Ontario, Canada
| | - Robel Yosief
- Department of Chemistry, York University, Toronto, Ontario, Canada
- Centre for Research on Biomolecular Interactions, York University, Toronto, Ontario, Canada
| | - Vasilij Koshkin
- Department of Chemistry, York University, Toronto, Ontario, Canada
- Centre for Research on Biomolecular Interactions, York University, Toronto, Ontario, Canada
| | - Yumin Qiu
- Centre for Research on Biomolecular Interactions, York University, Toronto, Ontario, Canada
- Department of Biology, York University, Toronto, Ontario, Canada
| | - Chun Peng
- Centre for Research on Biomolecular Interactions, York University, Toronto, Ontario, Canada
- Department of Biology, York University, Toronto, Ontario, Canada
| | - Vadim Elisseev
- IBM Research Europe, The Hartree Centre, Daresbury Laboratory, Warrington, United Kingdom
- Wrexham Glyndwr University, Wrexham, United Kingdom
| | - Sergey N Krylov
- Department of Chemistry, York University, Toronto, Ontario, Canada
- Centre for Research on Biomolecular Interactions, York University, Toronto, Ontario, Canada
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