Molecular control of cell density-mediated exit to quiescence

Leong

et al. 2022

Sci Rep

External signaling controls cell-cycle entry until cells irreversibly commit to the cell cycle to ensure faithful DNA replication. This process is tightly regulated by cyclin-dependent kinases (CDKs) and the retinoblastoma protein (Rb). Here, using live-cell sensors for CDK4/6 and CDK2 activities, we propose that CDK4/6 initiates Rb inactivation and CDK2 activation, which coordinates the timing of cell-cycle commitment and sequential G1/S transition. Our data show that CDK4/6 activation induces Rb inactivation and thereby E2F activation, driving a gradual increase in CDK2 activity. We found that rapid CDK4/6 inhibition can reverse cell-cycle entry until CDK2 activity reaches to high levels. This suggests that high CDK2 activity is required to initiate CDK2-Rb positive feedback and CDK4/6-indpendent cell-cycle progression. Since CDK2 activation also facilitates initiation of DNA replication, the timing of CDK2-Rb positive feedback is coupled with the G1/S transition. Our experiments, which acutely increased CDK2 activity by cyclin E1 overexpression, indicate that cells commit to the cell cycle before triggering DNA replication. Together, our data suggest that CDK4/6 inactivates Rb to begin E2F and CDK2 activation, and high CDK2 activity is necessary and sufficient to generate a bistable switch for Rb phosphorylation before DNA replication. These findings highlight how cells initiate the cell cycle and subsequently commit to the cell cycle before the G1/S transition.

Section: Discussionmentioning

confidence: 56%

Section: Discussionmentioning

confidence: 56%

CDK4/6 initiates Rb inactivation and CDK2 activity coordinates cell-cycle commitment and G1/S transition

Leong

et al. 2022

Sci Rep

“…6B, inset). The G1/S transition has a steep dependence on cyclin D concentration (Fan and Meyer, 2021) so it is possible that small changes in cyclin D concentration are sufficient to arrest the cell cycle. Furthermore, cyclin D is strongly post transcriptionally regulated by degradation (Alao, 2007).…”

Section: Resultsmentioning

confidence: 99%

Tissue confinement regulates cell growth and size in epithelia

Devany

Falk

Holt

et al. 2022

Preprint

SummaryCell proliferation is central process in tissue development, homeostasis and disease. Yet how proliferation is regulated in the tissue context remains poorly understood. Here, we introduce a quantitative framework to elucidate how tissue growth dynamics regulate cell proliferation. We show that tissue growth causes confinement that suppresses cell growth; however, this confinement does not directly affect the cell cycle. This leads to uncoupling between rates of cell growth and division in epithelia and, thereby, reduces cell size. Division becomes arrested at a minimal cell size, which is consistent across diverse epithelia in vivo. Here, the nucleus approaches a volume limit set by the compacted genome. The loss of Cyclin D1-dependent cell size regulation results in an abnormally high nuclear-to-cytoplasmic volume ratio and DNA damage. Overall, we demonstrate how epithelial proliferation is regulated by the interplay between tissue confinement and cell size regulation.Highlights- In epithelia, regulation of cell growth and cycle are uncoupled- Cell growth is regulated by tissue-scale dynamics, which determine confinement- Cell volume in epithelial tissue is described by G1 sizer model with a tunable growth rate- Volume of cells in epithelial tissues is near a minimum set by genome size

“…Heterogeneity and plasticity in cancer cells enables them to adapt in response to therapy. Even in the absence of genetic mutations, other heritable variation serves as a substrate for selection 45,46 . In this paper, we introduced a tree-based hidden Markov model that clusters single cells from a heterogeneous population based solely on their phenotypic traits and relationships.…”

Section: Discussionmentioning

confidence: 99%

A lineage tree-based hidden Markov model to quantify cellular heterogeneity and plasticity

Mohammadi

Visagan

Gross

et al. 2021

Preprint

Cell plasticity, or the ability of cells within a population to reversibly alter their phenotype, is an important feature of tissue homeostasis during processes such as wound healing and cancer. Plasticity operates alongside other sources of cell-to-cell heterogeneity such as genetic mutations and variation in signaling. Ultimately these processes prevent most cancer therapies from being curative. The predominant methods of quantifying tumor-drug response operate on snapshot population-level measurements and therefore lack evolutionary dynamics, which are particularly critical for dynamic processes such as plasticity. Here we apply a tree-based adaptation of a hidden Markov model (tHMM) that employs single cell lineages as input to learn the characteristic patterns of single cell heterogeneity and state transitions in an unsupervised fashion. This model enables single cell classification based on the phenotype of individual cells and their relatives for improved specificity in pinpointing the structure and dynamics of variability in drug response. Integrating this model with a modular interface for defining observed phenotypes allows the model to easily be adapted to any phenotype measured in single cells. To benchmark our model, we paired cell fate with either cell lifetimes or individual cell cycle phase lengths (G1 and S/G2) as our observed phenotypes on synthetic data and demonstrated that the model successfully classifies cells within experimentally tractable dataset sizes. As an application, we analyzed experimental measurements of cell fate and phase duration in cancer cell populations treated with chemotherapies to determine the number of distinct subpopulations. In total, this tHMM framework allows for the flexible classification of single cell heterogeneity across lineages.