Quantitative imaging with Fucci and mathematics to uncover temporal dynamics of cell cycle progression

Saitou, Takashi; Imamura, Takeshi

doi:10.1111/dgd.12252

Cited by 17 publications

(12 citation statements)

References 76 publications

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“…Practically, the FastFUCCI imaging workflow is supported by objects or events, conferring the statistical power necessary to detect subtle, transient or rapid real-time dynamics (Hamilton, 2009). Extraction of multidimensional data at such a scale would be a resource for studies attempting to integrate the FUCCI technology with mathematical modelling (Saitou and Imamura, 2016). Equally, addition of other imaging features, such as shape recognition, to the workflow would further diversify its experimental applications.…”

Section: Discussionmentioning

confidence: 99%

A quantitative FastFUCCI assay defines cell cycle dynamics at a single-cell level

Koh

Mascalchi

Rodríguez

et al. 2017

Journal of Cell Science

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The fluorescence ubiquitination-based cell cycle indicator (FUCCI) is a powerful tool for use in live cells but current FUCCI-based assays have limited throughput in terms of image processing and quantification. Here, we developed a lentiviral system that rapidly introduced FUCCI transgenes into cells by using an all-in-one expression cassette, FastFUCCI. The approach alleviated the need for sequential transduction and characterisation, improving labelling efficiency. We coupled the system to an automated imaging workflow capable of handling large datasets. The integrated assay enabled analyses of single-cell readouts at high spatiotemporal resolution. With the assay, we captured in detail the cell cycle alterations induced by antimitotic agents. We found that treated cells accumulated at G2 or M phase but eventually advanced through mitosis into the next interphase, where the majority of cell death occurred, irrespective of the preceding mitotic phenotype. Some cells appeared viable after mitotic slippage, and a fraction of them subsequently re-entered S phase. Accordingly, we found evidence that targeting the DNA replication origin activity sensitised cells to paclitaxel. In summary, we demonstrate the utility of the FastFUCCI assay for quantifying spatiotemporal dynamics and identify its potential in preclinical drug development.

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Section: Discussionmentioning

confidence: 99%

A quantitative FastFUCCI assay defines cell cycle dynamics at a single-cell level

Koh

Mascalchi

Rodríguez

et al. 2017

Journal of Cell Science

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“…Understanding of the complexity of cell-cycle dynamics and of the specific patterns of cell-cycle progression remains incomplete. Quantitative dynamic imaging combined with mathematical modelling has become an essential approach to understanding such complex dynamics [13]. The recently developed experimental FUCCI (fluorescent ubiquitination-based cell-cycle indicator) reporter system [14, 15] allows continuous imaging of cell-cycle progression in single live cells.…”

Section: Introductionmentioning

confidence: 99%

Mathematical modelling reveals unexpected inheritance and variability patterns of cell cycle parameters in mammalian cells

et al. 2019

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The cell cycle is the fundamental process of cell populations, it is regulated by environmental cues and by intracellular checkpoints. Cell cycle variability in clonal cell population is caused by stochastic processes such as random partitioning of cellular components to progeny cells at division and random interactions among biomolecules in cells. One of the important biological questions is how the dynamics at the cell cycle scale, which is related to family dependencies between the cell and its descendants, affects cell population behavior in the long-run. We address this question using a “mechanistic” model, built based on observations of single cells over several cell generations, and then extrapolated in time. We used cell pedigree observations of NIH 3T3 cells including FUCCI markers, to determine patterns of inheritance of cell-cycle phase durations and single-cell protein dynamics. Based on that information we developed a hybrid mathematical model, involving bifurcating autoregression to describe stochasticity of partitioning and inheritance of cell-cycle-phase times, and an ordinary differential equation system to capture single-cell protein dynamics. Long-term simulations, concordant with in vitro experiments, demonstrated the model reproduced the main features of our data and had homeostatic properties. Moreover, heterogeneity of cell cycle may have important consequences during population development. We discovered an effect similar to genetic drift, amplified by family relationships among cells. In consequence, the progeny of a single cell with a short cell cycle time had a high probability of eventually dominating the population, due to the heritability of cell-cycle phases. Patterns of epigenetic heritability in proliferating cells are important for understanding long-term trends of cell populations which are either required to provide the influx of maturing cells (such as hematopoietic stem cells) or which started proliferating uncontrollably (such as cancer cells).

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“…Furthermore, the PCNA-based approach also provides an accurate methodology for locating cell cycle transitions and commitment points 12,21,76 . This method provides an advantage over the widely-used fluorescence ubiquitin cell cycle indicator (FUCCI) system 77,78,76,79 , a quantitative ubiquitinationbased fluorescence reporter that uses tagged Cdt1 and geminin fragments to report the G1 and S-G2-M phases in real time. Whereas the FUCCI system is only capable of segmenting the cell cycle into 2 phases-G1 and S-G2-M 77-79 -and is not capable of sharply demarcating the G1/S transition 76 , the PCNA-based method provides a finer resolution demarking the boundaries at the G1/S and S/G2 borders 76 .…”

Section: Discussionmentioning

confidence: 99%

DNA damage checkpoint dynamics drive cell cycle phase transitions

Chao

Poovey

Privette

et al. 2017

Preprint

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DNA damage checkpoints are cellular mechanisms that protect the integrity of the genome during cell cycle progression. In response to genotoxic stress, these checkpoints halt cell cycle progression until the damage is repaired, allowing cells enough time to recover from damage before resuming normal proliferation. Here, we investigate the temporal dynamics of DNA damage checkpoints in individual proliferating cells by observing cell cycle phase transitions following acute DNA damage. We find that in gap phases (G1 and G2), DNA damage triggers an abrupt halt to cell cycle progression in which the duration of arrest correlates with the severity of damage. However, cells that have already progressed beyond a proposed "commitment point" within a given cell cycle phase readily transition to the next phase, revealing a relaxation of checkpoint stringency during later stages of certain cell cycle phases. In contrast to G1 and G2, cell cycle progression in S phase is significantly less sensitive to DNA damage. Instead of exhibiting a complete halt, we find that increasing DNA damage doses leads to decreased rates of S-phase progression followed by arrest in the subsequent G2. Moreover, these phase-specific differences in DNA damage checkpoint dynamics are associated with corresponding differences in the proportions of irreversibly arrested cells. Thus, the precise timing of DNA damage determines the sensitivity, rate of cell cycle progression, and functional outcomes for damaged cells. These findings should inform our understanding of cell fate decisions after treatment with common cancer therapeutics such as genotoxins or spindle poisons, which often target cells in a specific cell cycle phase.Recent live-imaging studies in single cells have shed light on some of the underlying parameters that confer differential sensitivity to endogenous DNA damage. For example, cell-to-cell variation in p21 levels leads to differences in checkpoint stringency (i.e., the robustness of cell cycle arrest in response to DNA damage) 11,12 .However, the underlying parameters that result in differential responses within a cell cycle phase and in response to exogenous DNA damage are generally unknown. Knowledge of these collective dynamical behaviors-which we refer to as DNA damage checkpoint dynamics-is necessary for understanding the relationship between the DNA damage response and functional cellular outcomes such as permanent cell cycle arrest. From a translational perspective, understanding DNA damage checkpoint dynamics could help explain the variability in cellular responses to many chemotherapeutic drugs, which act mainly by inducing DNA damage and interfering with cancer cell proliferation.Among the various forms of DNA damage, DNA double strand breaks (DSBs) are one of the most harmful types of lesions 13,14 . DSBs can give rise to chromosome rearrangements and deletions that can subsequently lead to cancer. The functional effects of DSBs can vary depending on the cell cycle phase in which the damage was incurred. For example, it ha...

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Quantitative imaging with Fucci and mathematics to uncover temporal dynamics of cell cycle progression

Cited by 17 publications

References 76 publications

A quantitative FastFUCCI assay defines cell cycle dynamics at a single-cell level

A quantitative FastFUCCI assay defines cell cycle dynamics at a single-cell level

Mathematical modelling reveals unexpected inheritance and variability patterns of cell cycle parameters in mammalian cells

DNA damage checkpoint dynamics drive cell cycle phase transitions

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