scholarly journals Evolution of Regulatory Complexity for Cell-Cycle Control

2021 ◽  
Author(s):  
Sam H. A. von der Dunk ◽  
Berend Snel ◽  
Paulien Hogeweg
Keyword(s):  
Cell Cycle ◽  
Gene Regulation ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Caulobacter Crescentus ◽  
Genome Structure ◽  
Cell Cycle Checkpoint ◽  
Evolutionary Strategies ◽  
Nutrient Levels ◽  
Gene Regulatory

How complexity arises is a fundamental evolutionary question. Complex gene regulation is thought to arise by the interplay between adaptive and non-adaptive forces at multiple organizational levels. Using a computational model, we investigate how complexity arises in cell-cycle regulation. Starting from the well-known Caulobacter crescentus network, we study how cells adapt their cell-cycle behaviour to a gradient of limited nutrient conditions using 10 replicate in silico evolution experiments. We find adaptive expansion of the gene regulatory network: improvement of cell-cycle behaviour allows cells to overcome the inherent cost of complexity. Replicates traverse different evolutionary trajectories leading to distinct eco-evolutionary strategies. In four replicates, cells evolve a generalist strategy to cope with a variety of nutrient levels; in two replicates, different specialist cells evolve for specific nutrient levels; in the remaining four replicates, an intermediate strategy evolves. The generalist and specialist strategies are contingent on the regulatory mechanisms that arise early in evolution, but they are not directly linked to network expansion and overall fitness. This study shows that functionality of cells depends on the combination of gene regulatory network topology and genome structure. For example, the positions of dosage-sensitive genes are exploited to signal to the regulatory network when replication is completed, forming a de novo evolved cell-cycle checkpoint. Complex gene regulation can arise adaptively both from expansion of the regulatory network and from the genomic organization of the elements in this network, demonstrating that to understand complex gene regulation and its evolution, it is necessary to integrate systems that are often studied separately.

Analysis of Hypoxiamir-Gene Regulatory Network Identifies Critical MiRNAs Influencing Cell-Cycle Regulation Under Hypoxic Conditions

MicroRNA ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 223-236 ◽  
Author(s):  
Apoorv Gupta ◽  
Sugadev Ragumani ◽  
Yogendra Kumar Sharma ◽  
Yasmin Ahmad ◽  
Pankaj Khurana
Keyword(s):  
Cell Cycle ◽  
Gene Regulatory Network ◽  
Stress Responses ◽  
Regulatory Network ◽  
Topological Analysis ◽  
Functional Characterization ◽  
Cell Cycle Checkpoint ◽  
Hypoxic Stress ◽  
Pathway Enrichment ◽  
Gene Regulatory

Background: Hypoxia is a pathophysiological condition which arises due to low oxygen concentration in conditions like cardiovascular diseases, inflammation, ascent to higher altitude, malignancies, deep sea diving, prenatal birth, etc. A number of microRNAs (miRNAs), Transcription Factors (TFs) and genes have been studied separately for their role in hypoxic adaptation and controlling cell-cycle progression and apoptosis during this stress. Objective: We hypothesize that miRNAs and TFs may act in conjunction to regulate a multitude of genes and play a crucial and combinatorial role during hypoxia-stress-responses and associated cellcycle control mechanisms. Method: We collected a comprehensive and non-redundant list of human hypoxia-responsive miRNAs (also known as hypoxiamiRs). Their experimentally validated gene-targets were retrieved from various databases and a comprehensive hypoxiamiR-gene regulatory network was built. Results: Functional characterization and pathway enrichment of genes identified phospho-proteins as enriched nodes. The phospho-proteins which were localized both in the nucleus and cytoplasm and could potentially play important role as signaling molecules were selected; and further pathway enrichment revealed that most of them were involved in NFkB signaling. Topological analysis identified several critical hypoxiamiRs and network perturbations confirmed their importance in the network. Feed Forward Loops (FFLs) were identified in the subnetwork of enriched genes, miRNAs and TFs. Statistically significant FFLs consisted of four miRNAs (hsa-miR-182-5p, hsa- miR-146b-5p, hsa-miR-96, hsa-miR-20a) and three TFs (SMAD4, FOXO1, HIF1A) both regulating two genes (NFkB1A and CDKN1A). Conclusion: Detailed BioCarta pathway analysis identified that these miRNAs and TFs together play a critical and combinatorial role in regulating cell-cycle under hypoxia, by controlling mechanisms that activate cell-cycle checkpoint protein, CDKN1A. These modules work synergistically to regulate cell-proliferation, cell-growth, cell-differentiation and apoptosis during hypoxia. A detailed mechanistic molecular model of how these co-regulatory FFLs may regulate the cell-cycle transitions during hypoxic stress conditions is also put forth. These biomolecules may play a crucial and deterministic role in deciding the fate of the cell under hypoxic-stress.

scholarly journals The transcription factor Zic4 acts as a transdifferentiation switch

2021 ◽  
Author(s):  
Matthias Christian Vogg ◽  
Jaroslav Ferenc ◽  
Wanda Christa Buzgariu ◽  
Chrystelle Perruchoud ◽  
Panagiotis Papasaikas ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Transcription Factor ◽  
Gene Regulatory Network ◽  
Cell Fate ◽  
Regulatory Network ◽  
Molecular Mechanisms ◽  
Model System ◽  
Cell Identity ◽  
Transcriptional Switch ◽  
Gene Regulatory

The molecular mechanisms that maintain cell identities and prevent transdifferentiation remain mysterious. Interestingly, both dedifferentiation and transdifferentiation are transiently reshuffled during regeneration. Therefore, organisms that regenerate readily offer a fruitful paradigm to investigate the regulation of cell fate stability. Here, we used Hydra as a model system and show that Zic4 silencing is sufficient to induce transdifferentiation of tentacle into foot cells. We identified a Wnt-controlled Gene Regulatory Network that controls a transcriptional switch of cell identity. Furthermore, we show that this switch also controls the re-entry into the cell cycle. Our data indicate that maintenance of cell fate by a Wnt-controlled GRN is a key mechanism during both homeostasis and regeneration.

scholarly journals A Dynamic Gene Regulatory Network Model That Recovers the Cyclic Behavior of Arabidopsis thaliana Cell Cycle

2015 ◽  
Vol 11 (9) ◽  
pp. e1004486 ◽  
Author(s):  
Elizabeth Ortiz-Gutiérrez ◽  
Karla García-Cruz ◽  
Eugenio Azpeitia ◽  
Aaron Castillo ◽  
María de la Paz Sánchez ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Arabidopsis Thaliana ◽  
Gene Regulatory Network ◽  
Network Model ◽  
Regulatory Network ◽  
Cyclic Behavior ◽  
Gene Regulatory

scholarly journals Regulation of transcription reactivation dynamics exiting mitosis

2021 ◽  
Vol 17 (10) ◽  
pp. e1009354
Author(s):  
Sergio Sarnataro ◽  
Andrea Riba ◽  
Nacho Molina
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Control Cell ◽  
Core Gene ◽  
Regulation Of Transcription ◽  
Gene Regulatory

Proliferating cells experience a global reduction of transcription during mitosis, yet their cell identity is maintained and regulatory information is propagated from mother to daughter cells. Mitotic bookmarking by transcription factors has been proposed as a potential mechanism to ensure the reactivation of transcription at the proper set of genes exiting mitosis. Recently, mitotic transcription and waves of transcription reactivation have been observed in synchronized populations of human hepatoma cells. However, the study did not consider that mitotic-arrested cell populations progressively desynchronize leading to measurements of gene expression on a mixture of cells at different internal cell-cycle times. Moreover, it is not well understood yet what is the precise role of mitotic bookmarking on mitotic transcription as well as on the transcription reactivation waves. Ultimately, the core gene regulatory network driving the precise transcription reactivation dynamics remains to be identified. To address these questions, we developed a mathematical model to correct for the progressive desynchronization of cells and estimate gene expression dynamics with respect to a cell-cycle pseudotime. Furthermore, we used a multiple linear regression model to infer transcription factor activity dynamics. Our analysis allows us to characterize waves of transcription factor activities exiting mitosis and predict a core gene regulatory network responsible of the transcription reactivation dynamics. Moreover, we identified more than 60 transcription factors that are highly active during mitosis and represent new candidates of mitotic bookmarking factors which could be relevant therapeutic targets to control cell proliferation.

scholarly journals Construction and Clarification of Dynamic Gene Regulatory Network of Cancer Cell Cycle via Microarray Data

2006 ◽  
Vol 2 ◽  
pp. 117693510600200 ◽  
Author(s):  
Cheng-Wei Li ◽  
Yung-Hsiang Chu ◽  
Bor-Sen Chen
Keyword(s):  
Cell Cycle ◽  
Hela Cell ◽  
Dynamic Model ◽  
Gene Regulatory Network ◽  
Cancer Cell ◽  
Microarray Data ◽  
Regulatory Network ◽  
Target Genes ◽  
Expression Profiles ◽  
Gene Regulatory

Background Cell cycle is an important clue to unravel the mechanism of cancer cells. Recently, expression profiles of cDNA microarray data of Cancer cell cycle are available for the information of dynamic interactions among Cancer cell cycle related genes. Therefore, it is more appealing to construct a dynamic model for gene regulatory network of Cancer cell cycle to gain more insight into the infrastructure of gene regulatory mechanism of cancer cell via microarray data. Results Based on the gene regulatory dynamic model and microarray data, we construct the whole dynamic gene regulatory network of Cancer cell cycle. In this study, we trace back upstream regulatory genes of a target gene to infer the regulatory pathways of the gene network by maximum likelihood estimation method. Finally, based on the dynamic regulatory network, we analyze the regulatory abilities and sensitivities of regulatory genes to clarify their roles in the mechanism of Cancer cell cycle. Conclusions Our study presents a systematically iterative approach to discern and characterize the transcriptional regulatory network in Hela cell cycle from the raw expression profiles. The transcription regulatory network in Hela cell cycle can also be confirmed by some experimental reviews. Based on our study and some literature reviews, we can predict and clarify the E2F target genes in G1/S phase, which are crucial for regulating cell cycle progression and tumorigenesis. From the results of the network construction and literature confirmation, we infer that MCM4, MCM5, CDC6, CDC25A, UNG and E2F2 are E2F target genes in Hela cell cycle.

scholarly journals Regulation of transcription reactivation dynamics exiting mitosis

2020 ◽  
Author(s):  
Sergio Sarnataro ◽  
Andrea Riba ◽  
Nacho Molina
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Control Cell ◽  
Core Gene ◽  
Regulation Of Transcription ◽  
Gene Regulatory

AbstractProliferating cells experience a global reduction of transcription during mitosis, yet their cell identity is maintained and regulatory information is propagated from mother to daughter cells. Mitotic bookmarking by transcription factors has been proposed as a potential mechanism to ensure the reactivation of transcription at the proper set of genes exiting mitosis. Recently, mitotic transcription and waves of transcription reactivation have been observed in synchronized populations of human hepatoma cells. However, the study did not consider that mitotic-arrested cell populations progressively desynchronize leading to measurements of gene expression on a mixture of cells at different internal cell-cycle times. Moreover, it is not well understood yet what is the precise role of mitotic bookmarking on mitotic transcription as well as on the transcription reactivation waves. Ultimately, the core gene regulatory network driving the precise transcription reactivation dynamics remains to be identified. To address these questions, we developed a mathematical model to correct for the progressive desynchronization of cells and estimate gene expression dynamics with respect to a cell-cycle pseudotime. Furthermore, we used a multiple linear regression model to infer transcription factor activity dynamics. Our analysis allows us to characterize waves of transcription factor activities exiting mitosis and identify a core gene regulatory network responsible of the transcription reactivation dynamics. Moreover, we identified more than 60 transcription factors that are highly active during mitosis and represent new candidates of mitotic bookmarking factors which could represent relevant therapeutic targets to control cell proliferation.

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