CellMAPtracer: A User-Friendly Tracking Tool for Long-Term Migratory and Proliferating Cells Associated with FUCCI Systems

Abstract

Cell migration is a fundamental biological process of key importance in health and disease. Advances in imaging techniques have paved the way to monitor cell motility. An ever-growing collection of computational tools to track cells has improved our ability to analyze moving cells. One renowned goal in the field is to provide tools that track cell movement as comprehensively and automatically as possible. However, fully automated tracking over long intervals of time is challenged by dividing cells, thus calling for a combination of automated and supervised tracking. Furthermore, after the emergence of various experimental tools to monitor cell-cycle phases, it is of relevance to integrate the monitoring of cell-cycle phases and motility. We developed CellMAPtracer, a multiplatform tracking system that achieves that goal. It can be operated as a conventional, automated tracking tool of single cells in numerous imaging applications. However, CellMAPtracer also allows adjusting tracked cells in a semiautomated supervised fashion, thereby improving the accuracy and facilitating the long-term tracking of migratory and dividing cells. CellMAPtracer is available with a user-friendly graphical interface and does not require any coding or programming skills. CellMAPtracer is compatible with two- and three-color fluorescent ubiquitination-based cell-cycle indicator (FUCCI) systems and allows the user to accurately monitor various migration parameters throughout the cell cycle, thus having great potential to facilitate new discoveries in cell biology.

Initial refinement of data from video-based single-cell tracking

“…Further development of sensors and software will extend the above restriction to data on cell positions, division, and dead. This will advance exploitation of its potential utility, as indicated by several authors (Van Valen et al, 2016;Tsai et al, 2019;Moen et al, 2019;Liu et al, 2020;Ghannoum et al, 2021). Single-cell tracking from high quality imagery allows collecting data on phenotypical changes, otherwise difficult to measure from an end-point measurement such as single-cell RNA-sequencing (scRNA-seq) (Liu et al, 2020).…”

“…Several authors emphasize that single-cell tracking from video has broadened the spectrum in mammalian signalling networks, drug development and cancer research (Regot et al, 2014; Suman et al, 2016; Van Valen et al, 2016; Koh et al, 2017; DuChez, 2018; Korsnes and Korsnes, 2018; Emami et al, 2020; Fujimoto et al, 2020; Fazeli et al, 2020; Ghannoum et al, 2021). Korsnes and Korsnes (2015, 2017, 2018) showed statistics from systematic single-cell tracking during several days, elucidating heterogeneous cell response and induction of cell death mechanisms.…”

FUCCItrack: An all-in-one software for single cell tracking and cell cycle analysis

“…We tested our tracking method with a publicly available FUCCI2 dataset ( https://doi.org/10.5281/zenodo.4179316 ) and could not measure any significant differences with CellMAPtracer [ 19 ] ( S1 Fig ).…”

“…The image contains the mCherry channel in red, mVenus in green and the overlay of cell trajectories in blue. ( B ) The ground truth or reference annotation of the “FUCCI-2channels” provided by the authors of the tool CellMAPtracer [ 19 ]. ( C ) Coordinates difference (in μm) between the FUCCItrack tracking and the true coordinates on the x and y axes based on the ground truth of CellMAPtracer (n = 8 cells during 61 frames each).…”

“…To the best of our knowledge, only three software have been reported to treat FUCCI time-lapse datasets in an automatic or semi-automatic way [ 19 – 21 ]. One is not publicly available [ 21 ], one requires multiples applications to be run (Fiji and Columbus) [ 20 ], and the latest one was released recently on MATLAB [ 19 ]. The latter can perform migration analysis and includes a FUCCI plug-in to extract nuclear intensity and obtain cell cycle duration.…”