scholarly journals Mechanisms of signalling-memory governing progression through the eukaryotic cell cycle

2020 ◽  
Author(s):  
Béla Novák ◽  
John J Tyson
Keyword(s):  
Cell Cycle ◽  
Network Motif ◽  
Eukaryotic Cell ◽  
Cycle Phase ◽  
Restriction Point ◽  
Negative Feedback Loops ◽  
Signalling Network ◽  
Positive And Negative Feedback ◽  
Biochemical State ◽  
Pass Through

AbstractAs cells pass through each replication-division cycle, they must be able to postpone further progression if they detect any threats to genome integrity, such as DNA damage or misaligned chromosomes. Once a ‘decision’ is made to proceed, the cell unequivocally enters into a qualitatively different biochemical state, which makes the transitions from one cell cycle phase to the next switch-like and irreversible. Each transition is governed by a unique signalling network; nonetheless, they share a common characteristic of bistable behaviour, a hallmark of molecular memory devices. Comparing the cell cycle signalling mechanisms acting at the Restriction Point, G1/S, G2/M and meta-to-anaphase transitions, we deduce a generic network motif of coupled positive and negative feedback loops underlying each transition.

scholarly journals Unreplicated DNA remaining from unperturbed S phases passes through mitosis for resolution in daughter cells

2016 ◽  
Vol 113 (39) ◽  
pp. E5757-E5764 ◽  
Author(s):  
Alberto Moreno ◽  
Jamie T. Carrington ◽  
Luca Albergante ◽  
Mohammed Al Mamun ◽  
Emma J. Haagensen ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Eukaryotic Cell ◽  
Nuclear Bodies ◽  
Genome Replication ◽  
Replication Forks ◽  
Replication Origins ◽  
Theoretical Predictions ◽  
Fork Stalling ◽  
Theoretical Evidence ◽  
Pass Through

To prevent rereplication of genomic segments, the eukaryotic cell cycle is divided into two nonoverlapping phases. During late mitosis and G1 replication origins are “licensed” by loading MCM2-7 double hexamers and during S phase licensed replication origins activate to initiate bidirectional replication forks. Replication forks can stall irreversibly, and if two converging forks stall with no intervening licensed origin—a “double fork stall” (DFS)—replication cannot be completed by conventional means. We previously showed how the distribution of replication origins in yeasts promotes complete genome replication even in the presence of irreversible fork stalling. This analysis predicts that DFSs are rare in yeasts but highly likely in large mammalian genomes. Here we show that complementary strand synthesis in early mitosis, ultrafine anaphase bridges, and G1-specific p53-binding protein 1 (53BP1) nuclear bodies provide a mechanism for resolving unreplicated DNA at DFSs in human cells. When origin number was experimentally altered, the number of these structures closely agreed with theoretical predictions of DFSs. The 53BP1 is preferentially bound to larger replicons, where the probability of DFSs is higher. Loss of 53BP1 caused hypersensitivity to licensing inhibition when replication origins were removed. These results provide a striking convergence of experimental and theoretical evidence that unreplicated DNA can pass through mitosis for resolution in the following cell cycle.

scholarly journals The concepts of Ludwik Fleck and their application to the eukaryotic cell cycle

2017 ◽  
Vol 16 ◽  
pp. 335-364 ◽  
Author(s):  
Stephen Cooper ◽  
◽  
Keyword(s):  
Cell Cycle ◽  
Regulatory Element ◽  
Current Model ◽  
Eukaryotic Cell ◽  
Dependent Manner ◽  
Ludwik Fleck ◽  
Restriction Point ◽  
Thought Collective ◽  
Cycle Dependent ◽  
Scientific Ideas

The concepts of Ludwik Fleck (1896–1961), a microbiologist, historian, and philosopher of medicine, can be used to analyze the conservative nature of scientific ideas. This is discussed and applied to ideas dominant in the understanding of the eukaryotic cell cycle. These are (a) the G1-phase restriction point as a regulatory element of the mammalian cell cycle, (b) the Rate Change Point proposed to exist in fission yeast, and (c) the proposal that a large number of genes are expressed in a cell-cycle-dependent manner. Fleck proposed that scientific ideas become fixed and difficult to change because criticisms of current and dominant models are either ignored or turned to support of the current model. The idea of a thought-collective leading to the stability of scientific ideas is a central theme of the theory of Ludwik Fleck.

Growth and cell cycle phase composition of fibroblasts in the reconstituted dermis model.

1990 ◽  
Vol 52 (5) ◽  
pp. 986-992
Author(s):  
Takeshi KONO ◽  
Tsukasa TANII ◽  
Masayoshi FURUKAWA ◽  
Nobuyuki MIZUNO ◽  
Shoji TANIGUCHI ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Phase Composition ◽  
Cell Cycle Phase ◽  
Cycle Phase

Molecular Mechanisms of Thymoquinone as Anticancer agent

2020 ◽  
Vol 23 ◽  
Author(s):  
Fatma Ismail Alhmied ◽  
Ali Hassan Alammar ◽  
Bayan Mohammed Alsultan ◽  
Marooj Alshehri ◽  
Faheem Hyder Pottoo
Keyword(s):  
Breast Cancer ◽  
Cell Cycle ◽  
Cell Cycle Arrest ◽  
Human Breast Cancer ◽  
Phase Cell ◽  
Cycle Phase ◽  
Human Breast ◽  
Cycle Arrest ◽  
Phase Arrest ◽  
Anti Cancer

Abstract:: Thymoquinone (TQ), the bioactive constituent of Nigella Sativa seeds is a well-known natural compound for the management of several types of cancers. The anti-cancer properties of thymoquinone are thought to be operated via intervening with various oncogenic pathways including cell cycle arrest, prevention of inflammation and oxidative stress, induction of invasion, metastasis, inhibition of angiogenesis, and apoptosis. As well as up-regulation and down-regulation of specific tumor suppressor genes and tumor promoting genes, respectively. Proliferation of various tumor cells is inhibited by TQ via induction of cell cycle arrest, disruption of the microtubule organization, and down regulating cell survival protein expression. TQ induces G1 phase cell cycle arrest in human breast cancer, colon cancer and osteosarcoma cells through inhibiting the activation of cyclin E or cyclin D and up-regulating p27and p21 a cyclin dependent kinase (Cdk) inhibitor. TQ concentration is a significant factor in targeting a particular cell cycle phase. While high concentration of TQ induced G2 phase arrest in human breast cancer (MCF-7) cells, low concentration causes S phase arrest. This review article provides mechanistic insights into the anti-cancer properties of thymoquinone.

Cell Cycle and Cancer: The G1 Restriction Point and the G1 / S Transition

2002 ◽  
Vol 3 (4) ◽  
pp. 245-263 ◽  
Author(s):  
S. Ortega ◽  
M. Malumbres ◽  
M. Barbacid
Keyword(s):  
Cell Cycle ◽  
Restriction Point

scholarly journals An Imbalanced Image Classification Method for the Cell Cycle Phase

Information ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 249
Author(s):  
Xin Jin ◽  
Yuanwen Zou ◽  
Zhongbing Huang
Keyword(s):  
Cell Cycle ◽  
Deep Learning ◽  
Image Classification ◽  
Classification Accuracy ◽  
Data Augmentation ◽  
Cycle Phase ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Cellular Life

The cell cycle is an important process in cellular life. In recent years, some image processing methods have been developed to determine the cell cycle stages of individual cells. However, in most of these methods, cells have to be segmented, and their features need to be extracted. During feature extraction, some important information may be lost, resulting in lower classification accuracy. Thus, we used a deep learning method to retain all cell features. In order to solve the problems surrounding insufficient numbers of original images and the imbalanced distribution of original images, we used the Wasserstein generative adversarial network-gradient penalty (WGAN-GP) for data augmentation. At the same time, a residual network (ResNet) was used for image classification. ResNet is one of the most used deep learning classification networks. The classification accuracy of cell cycle images was achieved more effectively with our method, reaching 83.88%. Compared with an accuracy of 79.40% in previous experiments, our accuracy increased by 4.48%. Another dataset was used to verify the effect of our model and, compared with the accuracy from previous results, our accuracy increased by 12.52%. The results showed that our new cell cycle image classification system based on WGAN-GP and ResNet is useful for the classification of imbalanced images. Moreover, our method could potentially solve the low classification accuracy in biomedical images caused by insufficient numbers of original images and the imbalanced distribution of original images.

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