Lineage correlations of single cell division time as a probe of cell-cycle dynamics

Many common, important diseases are either caused or exacerbated by hyperactivation (e.g., cancer) or inactivation (e.g., heart failure) of the cell division cycle. A better understanding of the cell cycle is critical for interpreting numerous types of physiological changes in cells. Moreover, new insights into how to control it will facilitate new therapeutics for a variety of diseases and new avenues in regenerative medicine. The progression of cells through the four main phases of their division cycle [G0/G1, S (DNA synthesis), G2, and M (mitosis)] is a highly conserved process orchestrated by several pathways (e.g., transcription, phosphorylation, nuclear import/export, and protein ubiquitination) that coordinate a core cell cycle pathway. This core pathway can also receive inputs that are cell type and cell niche dependent. “Broken cell” methods (e.g., use of labeled nucleotide analogs) to assess for cell cycle activity have revealed important insights regarding the cell cycle but lack the ability to assess living cells in real time (longitudinal studies) and with single-cell resolution. Moreover, such methods often require cell synchronization, which can perturb the pathway under study. Live cell cycle sensors can be used at single-cell resolution in living cells, intact tissue, and whole animals. Use of these more recently available sensors has the potential to reveal physiologically relevant insights regarding the normal and perturbed cell division cycle.

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Publisher Correction: Osmotic pressure modulates single cell cycle dynamics inducing reversible growth arrest and reactivation of human metastatic cells

Scientific Reports ◽

10.1038/s41598-021-99039-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Hubert M. Taïeb ◽

Daniela S. Garske ◽

Jörg Contzen ◽

Manfred Gossen ◽

Luca Bertinetti ◽

...

Keyword(s):

Cell Cycle ◽

Single Cell ◽

Osmotic Pressure ◽

Growth Arrest ◽

Metastatic Cells ◽

Cell Cycle Dynamics

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Predicting Individual Cell Division Events from Single-Cell ERK and Akt Dynamics

10.1101/2021.09.14.460349 ◽

2021 ◽

Author(s):

Alan D Stern ◽

Gregory R Smith ◽

Luis C Santos ◽

Deepraj Sarmah ◽

Xiang Zhang ◽

...

Keyword(s):

Cell Cycle ◽

Cell Division ◽

Single Cell ◽

Cell Cycle Progression ◽

Time Window ◽

Single Cells ◽

Machine Learning Algorithms ◽

Cycle Progression ◽

Restriction Point ◽

Activity Dynamics

Predictive determinants of stochastic single-cell fates have been elusive, even for the well-studied mammalian cell cycle. What drives proliferation decisions of single cells at any given time? We monitored single-cell dynamics of the ERK and Akt pathways, critical cell cycle progression hubs and anti-cancer drug targets, and paired them to division events in the same single cells using the non-transformed MCF10A epithelial line. Following growth factor treatment, in cells that divide both ERK and Akt activities are significantly higher within the S-G2 time window (~8.5-40 hours). Such differences were much smaller in the pre-S-phase, restriction point window which is traditionally associated with ERK and Akt activity dependence, suggesting unappreciated roles for ERK and Akt in S through G2. Machine learning algorithms show that simple metrics of central tendency in this time window are most predictive for subsequent cell division; median ERK and Akt activities classify individual division events with an AUC=0.76. Surprisingly, ERK dynamics alone predict division in individual cells with an AUC=0.74, suggesting Akt activity dynamics contribute little to the decision driving cell division in this context. We also find that ERK and Akt activities are less correlated with each other in cells that divide. Network reconstruction experiments demonstrated that this correlation behavior was likely not due to crosstalk, as ERK and Akt do not interact in this context, in contrast to other transformed cell types. Overall, our findings support roles for ERK and Akt activity throughout the cell cycle as opposed to just before the restriction point, and suggest ERK activity dynamics are substantially more important than Akt activity dynamics for driving cell division in this non-transformed context. Single cell imaging along with machine learning algorithms provide a better basis to understand cell cycle progression on the single cell level.

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Dependence of fluorodeoxyglucose (FDG) uptake on cell cycle and dry mass: a single-cell study using a multi-modal radiography platform

10.1101/668392 ◽

2019 ◽

Author(s):

Yongjin Sung ◽

Marc-Andre Tetrault ◽

Kazue Takahashi ◽

Jinsong Ouyang ◽

Guillem Pratx ◽

...

Keyword(s):

Cell Cycle ◽

Cell Division ◽

Single Cell ◽

Hela Cells ◽

Building Blocks ◽

Dry Mass ◽

Proliferation Index ◽

Cycle Phase ◽

Proliferative Potential ◽

Fdg Uptake

AbstractHigh glucose uptake by cancer compared to normal tissues has long been utilized in fluorodeoxyglucose-based positron emission tomography (FDG-PET) as a contrast mechanism. The FDG uptake rate has been further related to the proliferative potential of cancer, specifically the proliferation index (PI) − the proportion of cells in S, G2 or M phases. The underlying hypothesis was that the cells preparing for cell division would consume more energy and metabolites as building blocks for biosynthesis. Despite the wide clinical use, mixed reports exist in the literature on the relationship between FDG uptake and PI. This may be due to the large variation in cancer types or methods adopted for the measurements. Of note, the existing methods can only measure the average properties of a tumor mass or cell population with highly-heterogeneous constituents. In this study, we have built a multi-modal live-cell radiography system and measured the [18F]FDG uptake by single HeLa cells together with their dry mass and cell cycle phase. The results show that HeLa cells take up twice more [18F]FDG in S, G2 or M phases than in G1 phase, which confirms the association between FDG uptake and PI at a single-cell level. Importantly, we show that [18F]FDG uptake and cell dry mass have a positive correlation in HeLa cells, which suggests that high [18F]FDG uptake in S, G2 or M phases can be largely attributed to increased dry mass, rather than the activities preparing for cell division. This interpretation is consistent with recent observations that the energy required for the preparation of cell division is much smaller than that for maintaining house-keeping proteins.

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Abstract 278: Metabolic Reprogramming is Essential for Cell Cycle Progression in Cardiomyocytes

Circulation Research ◽

10.1161/res.127.suppl_1.278 ◽

2020 ◽

Vol 127 (Suppl_1) ◽

Author(s):

Riham Abouleisa ◽

Lindsey McNally ◽

Qinghui Ou ◽

Krishna Choudhary ◽

Reuben Thomas ◽

...

Keyword(s):

Cell Cycle ◽

Cell Division ◽

Single Cell ◽

Cell Cycle Progression ◽

Biosynthetic Pathway ◽

Cyclin B1 ◽

Metabolic Reprogramming ◽

Cycle Progression ◽

Pathway Activity ◽

Nad Synthesis

Myocardial infarction causes irreversible loss of cardiomyocytes (CMs) and often leads to heart failure. To replace the lost cells, we identified a combination of cell-cycle regulators that induces stable cytokinesis in adult post-mitotic cells. Specifically, adenoviral overexpression of cyclin-dependent kinase 1 (CDK1), CDK4, cyclin B1, and cyclin D1 (collectively known as ‘four factors’, or simply 4F) induced cell division in ~15% of post-mitotic mouse, rat, and human CMs. Identifying the major roadblocks during the process of CM proliferation is a key for advancing this field. This was not possible before due to the lack of efficient methods to induce CM proliferation. The goal of the current study is to understand why a subpopulation of CMs divide while most CMs, despite expressing 4F, resist cell cycle reentry. To investigate transcriptional changes during cell cycle progression at the single cell level, we conducted temporal single cell RNAseq on 60-day-old matured hiPS-CMs infected with either LacZ (control) or 4F for 24, 48 and 72 h. We found a unique cell population that appears 48 h after infection with the 4F; this population was identified as the proliferating population and expressed high levels of cytokinesis genes (Ki67, Aurora Kinase A and B, E2F1, CDC20, ANLN, TK1, CCNA2, PLK1 and PCNA). Consistent with our published data, this population represents ~15% of the total CMs population expressing 4F. Compared with the quiescent population from the same sample, this unique population of proliferating CMs shows significant upregulation of the cell cycle program and major downregulation of mitochondrial electron transport chain genes. In line with these transcriptomic changes, hiPS-CMs had 50% lower rates of oxidative phosphorylation 48 h after 4F infection. Furthermore, in 4F-overexpressing iPS-CMs, stable isotope tracing demonstrated significantly higher enrichment of glucose-derived 13 C in NAD and UDP-HexNAc, suggesting activation of NAD synthesis and the hexosamine biosynthetic pathway. We conclude that proliferating CMs diminish catabolic pathway activity and augment biosynthetic pathway activity. The capacity of CM subpopulation to reprogram their metabolism is likely to facilitate their ability to complete cell division.

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Concurrent processes setE. colicell division

Science Advances ◽

10.1126/sciadv.aau3324 ◽

2018 ◽

Vol 4 (11) ◽

pp. eaau3324 ◽

Cited By ~ 21

Author(s):

Gabriele Micali ◽

Jacopo Grilli ◽

Matteo Osella ◽

Marco Cosentino Lagomarsino

Keyword(s):

Cell Cycle ◽

Cell Division ◽

Single Cell ◽

Chromosome Segregation ◽

Genetic Material ◽

Replication Initiation ◽

Concurrent Processes ◽

A Cell ◽

Rate Limiting ◽

Cell Data

A cell can divide only upon completion of chromosome segregation; otherwise, its daughters would lose genetic material. However, we do not know whether the partitioning of chromosomes is the key event for the decision to divide. We show how key trends in single-cell data reject the classic idea of replication-segregation as the rate-limiting process for cell division. Instead, the data agree with a model where two concurrent processes (setting replication initiation and interdivision time) set cell division on competing time scales. During each cell cycle, division is set by the slowest process (an “AND” gate). The concept of transitions between cell cycle stages as decisional processes integrating multiple inputs instead of cascading from orchestrated steps can affect the way we think of the cell cycle in general.

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