Cell Cycle Regulatory Network Research Articles

Structure of the DDB1-AMBRA1 E3 ligase receptor complex linked to cell cycle regulation

AMBRA1 is a tumor suppressor protein that functions as a substrate receptor of the ubiquitin conjugation system with roles in autophagy and the cell cycle regulatory network. The intrinsic disorder of AMBRA1 has thus far precluded its structural determination. To solve this problem, we analyzed the dynamics of AMBRA1 using hydrogen deuterium exchange mass spectrometry (HDX-MS). The HDX results indicated that AMBRA1 is a highly flexible protein and can be stabilized upon interaction with DDB1, the adaptor of the Cullin4A/B E3 ligase. Here, we present the cryo-EM structure of AMBRA1 in complex with DDB1 at 3.08 Å resolution. The structure shows that parts of the N- and C-terminal structural regions in AMBRA1 fold together into the highly dynamic WD40 domain and reveals how DDB1 engages with AMBRA1 to create a binding scaffold for substrate recruitment. The N-terminal helix-loop-helix motif and WD40 domain of AMBRA1 associate with the double-propeller fold of DDB1. We also demonstrate that DDB1 binding-defective AMBRA1 mutants prevent ubiquitination of the substrate Cyclin D1 in vitro and increase cell cycle progression. Together, these results provide structural insights into the AMBRA1-ubiquitin ligase complex and suggest a mechanism by which AMBRA1 acts as a hub involved in various physiological processes.

Decoding the lncRNAome Across Diverse Cellular Stresses Reveals Core p53-effector Pan-cancer Suppressive lncRNAs.

Identification of pan-cancer suppressive lncRNAs transcriptionally regulated by p53 across different cellular stresses by integrating multilayered high-throughput molecular profiles. This study provides critical new insights into the p53 tumor suppressor by revealing the lncRNAs in the p53 cell-cycle regulatory network and their impact on cancer cell growth and patient survival.

Fam72a functions as a cell-cycle-controlled gene during proliferation and antagonizes apoptosis through reprogramming PP2A substrates.

The cell cycle is key to life. After decades of research, it is unclear whether any parts of this process have yet to be identified. Fam72a is a poorly characterized gene and is evolutionarily conserved across multicellular organisms. Here, we have found that Fam72a is a cell-cycle-regulated gene that is transcriptionally and post-transcriptionally regulated by FoxM1 and APC/C, respectively. Functionally, Fam72a directly binds to tubulin and both the Aα and B56 subunits of PP2A-B56 to modulate tubulin and Mcl1 phosphorylation, which in turn affects the progression of the cell cycle and signaling of apoptosis. Moreover, Fam72a is involved in early responses to chemotherapy, and it efficiently antagonizes various anticancer compounds such as CDK and Bcl2 inhibitors. Thus, Fam72a switches the tumor-suppressive PP2A to be oncogenic by reprogramming its substrates. These findings identify a regulatory axis of PP2A and a protein member in the cell cycle and tumorigenesis regulatory network in human cells.

Abstract P3-10-01: Deciphering the heterogeneity of cell cycle in breast cancer and relevance to clinical application of CDK inhibitors

Abstract BACKGROUND: Deregulation of cellular proliferation represents a defining hallmark of cancer. The mechanisms driving aberrant cell cycle progression across different breast cancer subtypes is highly diverse and likely contributes to therapeutic resistance in a variety of contexts. The significance of cell cycle heterogeneity is most clear in the context of metastatic HR+/HER2- breast cancer, wherein acquired and intrinsic resistance to CDK4/6 inhibition represents a significant clinical challenge. However, aberrant cell cycle regulatory networks likely further confound the use of targeted therapies in the context of TNBC. METHODS AND RESULTS: We employed unbiased analyses of large number of breast cancer models to decipher the genetic requirements for different CDK and Cyclins which drive proliferation and the significance to response to CDK4/6 inhibitors. Breast cancer cells harbor heterogeneity in the requirement for a given G1/S regulatory CDK or Cyclin. These dependencies are conditioned by the expression of the respective CDK or Cyclin, as well as other gene expression or genetic features present within the tumor that could represent putative biomarkers. In general, conventional dependency for CDK4 and Cyclin D1 is strongest in HR+/HER2- breast cancer models, whereas TNBC exhibits dependency on a variety of different CDK or Cyclin genes. Resistance to CDK4/6 inhibitors in HR+/HER2- breast cancer models, while occurring through a number of different primary mechanisms, functionally deregulates the phosphorylation of RB. However, genetically enforcing RB activation is sufficient to block proliferation, underscoring the opportunity to ameliorate resistance to CDK inhibitory strategies. CRISPR screens in HR+/HER2- and TNBC models are identifying new mediators of sensitivity and resistance to CDK4/6 inhibitors. Inherently, elevated expression of Cyclin E and p16INK4A are associated with resistance to multiple therapeutic approaches, including CDK4/6 inhibitors, but denote a requirement for CDK2. The cell cycle conditions disparately dependent on CDK4/D1 vs. CDK2/E can be visualized by multispectral imaging and used to direct CDK inhibitor based strategies. CONCLUSIONS: Together these studies illustrate the complex nature of breast cancer cell cycles which can confound therapy. However, understanding of this heterogeneity can create new opportunities for precision approaches targeting CDK/Cyclin-dependence therapeutically. Citation Format: Erik S. Knudsen, Vishnu M. Kumarasamy, Jianxin Wang, Agnieszka Witkiewicz. Deciphering the heterogeneity of cell cycle in breast cancer and relevance to clinical application of CDK inhibitors [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-10-01.

A bioinformatics analysis for diagnostic roles of the E2F family in esophageal cancer.

Esophageal cancer (EC) is the eighth most commonly occurring cancer worldwide and the sixth leading cause of cancer-related deaths. The therapeutic effect of EC patients is not ideal, and new biomarkers are needed to guide diagnosis and prognosis of EC patients. E2F family transcription factors are among the most important links in the cell cycle regulatory network. E2Fs dysregulation not only promotes the early stages of tumor development but also the progression of benign tumors to malignant tumors. E2F is expected to be a new biomarker. The prognostic significance of the E2F family in EC requires further research. We analyzed The Cancer Genome Atlas (TCGA), Gene Expression Profiling Interactive Analysis (GEPIA), and GeneMANIA databases to obtain RNA-sequencing data and clinical data. The clinical data included age, gender, race, stage, type, status, etc. The prognosis outcome included overall survival (OS) and progression-free interval (PFI). Subsequently, we conducted further research on gene expressions, enrichment analysis, interaction network, and prognostic values by R software, containing ggplot2, ComplexHeatmap, DESeq2, pROC R package, based on t-test, Wilcoxon rank sum test, Spearman rank correlation analysis, log-rank test and COX model. We found that mRNA transcription levels of E2F1, E2F3-8 were more highly expressed in esophageal carcinoma (ESCA) tissues than in normal tissues. E2F8 expression was correlated with tumor stage [Pr(>F)=0.00856]. E2F-related genes played a role in development and differentiation, and were prevalent in the endoplasmic reticulum lumen, Golgi lumen, and lipoprotein particle, catalyzing translation activities and lipid metabolism. Each gene was found to be related to each other to some degree. The GeneMANIA network analysis revealed links between E2Fs and other genes. We compared the correlations between 24 kinds of tumor-infiltrating immune cells and E2Fs. E2F1 (AUC =0.945, CI: 0.890-1.000) and E2F7 (AUC =0.958, CI: 0.920-0.996) exhibited higher predictive power accuracy. However, only E2F7 was closely related to OS [HR =1.91 (1.16-3.16), P=0.011]. We discover that E2F7 is a prognostic biomarker. E2F family may take part in the development of EC through lipid metabolism pathways, which is helpful to predict the prognosis of EC patients and guide accurate diagnosis and treatment.

The Impact of Sleep Loss on Brain Function

•The principles of signal-based functioning of GRNs have been discussed in a wide range of contexts: from the simple bacteriophage λ lysis-lysogenic switch to the complex GRNs in humans comprising transcriptional regulatory networks, protein-protein interaction networks, and metabolic networks. The ultimate phenotypes of complex organisms result from functional GRNs, where the gene expression pattern is fundamentally regulated by the interactions of gene and environmental factors.•The first hint that multiple genes may work together came from the discovery of the phenomenon, Epistasis, the nonallelic interactions in gene functions. As an example, we have presented how the phenomenon of Epistasis is involved in the manifestation of AD. Understanding the GRNs involved in AD pathogenesis could be useful for designing effective therapeutics.•siRNA- and shRNA-mediated knockdown of genes followed by transcriptome analysis are the major tools for elucidating the GRN.•One of the most well-studied GRNs, with physiological and pathophysiological contexts, is the tumor suppressor and master cell cycle regulatory network, Rb pathway. The multifunctional Rb pathway seems to be involved in a wide range of physiological processes, from cell proliferation to cellular plasticity, through its interactions with more than 300 proteins and regulating the expression of a large number of genes, including epigenetic modulators. Understanding of RB1 pathway is guiding the discovery of targeted cancer therapeutics. A few of these have already received FDA approval to be used in the clinics.•Reversal of the epigenetic landscape is no longer a dream or fiction. It is proven today that the ectopic expression of 3–4 TFs can induce pluripotency in any differentiated cells. It is also possible to push the cells from one lineage to another by using these TFs. Most interestingly, this kind of cell reprogramming is also possible by a set of small molecule compounds targeting epigenetic enzymes, kinases, etc. These discoveries have created tremendous potential in drug discovery and regenerative medicines.

SOG1 transcription factor promotes the onset of endoreduplication under salinity stress in Arabidopsis

As like in mammalian system, the DNA damage responsive cell cycle checkpoint functions play crucial role for maintenance of genome stability in plants through repairing of damages in DNA and induction of programmed cell death or endoreduplication by extensive regulation of progression of cell cycle. ATM and ATR (ATAXIA-TELANGIECTASIA-MUTATED and -RAD3-RELATED) function as sensor kinases and play key role in the transmission of DNA damage signals to the downstream components of cell cycle regulatory network. The plant-specific NAC domain family transcription factor SOG1 (SUPPRESSOR OF GAMMA RESPONSE 1) plays crucial role in transducing signals from both ATM and ATR in presence of double strand breaks (DSBs) in the genome and found to play crucial role in the regulation of key genes involved in cell cycle progression, DNA damage repair, endoreduplication and programmed cell death. Here we report that Arabidopsis exposed to high salinity shows generation of oxidative stress induced DSBs along with the concomitant induction of endoreduplication, displaying increased cell size and DNA ploidy level without any change in chromosome number. These responses were significantly prominent in SOG1 overexpression line than wild-type Arabidopsis, while sog1 mutant lines showed much compromised induction of endoreduplication under salinity stress. We have found that both ATM-SOG1 and ATR-SOG1 pathways are involved in the salinity mediated induction of endoreduplication. SOG1was found to promote G2-M phase arrest in Arabidopsis under salinity stress by downregulating the expression of the key cell cycle regulators, including CDKB1;1, CDKB2;1, and CYCB1;1, while upregulating the expression of WEE1 kinase, CCS52A and E2Fa, which act as important regulators for induction of endoreduplication. Our results suggest that Arabidopsis undergoes endoreduplicative cycle in response to salinity induced DSBs, showcasing an adaptive response in plants under salinity stress.

Dynamical analysis of the fission yeast cell cycle via Markov chain.

The cell cycle is a complex network involved in the regulation of cell growth and proliferation. Intrinsic molecular noise in gene expression in the cell cycle network can generate fluctuations in protein concentration. How the cell cycle network maintains its robust transitions between cell cycle phases in the presence of these fluctuations remains unclear. To understand the complex and robust behavior of the cell cycle system in the presence of intrinsic noise, we developed a Markov model for the fission yeast cell cycle system. We quantified the effect of noise on gene and protein activity and on the probability of transition between different phases of the cell cycle. Our analysis shows how network perturbations decide the fate of the cell. Our model predicts that the cell cycle pathway (subsequent transitions from [Formula: see text]) is the most robust and probable pathway among all possible trajectories in the cell cycle network. We performed a sensitivity analysis to find correlations between protein interaction weights and transition probabilities between cell cycle phases. The sensitivity analysis predicts how network perturbations affect the transition probability between different cell cycle phases and, consequently, affect different cell fates, thus, forming testable in vitro/in vivo hypotheses. Our simulation results agree with published experimental findings and reveal how noise in the cell cycle regulatory network can affect cell cycle progression.

Angiotensin II-induced histone deacetylase 5 phosphorylation, nuclear export, and Egr-1 expression are mediated by Akt pathway in A10 vascular smooth muscle cells.

Angiotensin II (ANG II) regulates an array of physiological and pathological responses in vascular smooth muscle cells (VSMCs) by activating ERK1/2 and phosphoinositide 3-kinase (PI3K)/Akt signaling pathways. We have demonstrated that ANG II and insulin-like growth factor-1 (IGF-1) induce the expression of early growth response protein-1 (Egr-1), a zinc finger transcription factor, which regulates the transcription of cell cycle regulatory genes network in VSMCs. We have reported that IGF-1 induces the phosphorylation of histone deacetylase 5 (HDAC5), which has been implicated in the expression of genes linked to VSMC growth and hypertrophy, via a PI3K/Akt-dependent pathway in VSMCs. However, the involvement of PI3K/Akt pathways in ANG II-induced HDAC5 phosphorylation and the contribution of HDAC5 in Egr-1 expression and hypertrophy in VSMCs remain unexplored. Here, we show that pharmacological blockade of the PI3K/Akt pathway either by wortmannin/SC66 or siRNA-induced silencing of Akt attenuated ANG II-induced HDAC5 phosphorylation and its nuclear export. Moreover, SC66 or Akt knockdown also suppressed ANG II-induced Egr-1 expression. Furthermore, pharmacological inhibition of HDAC5 by MC1568 or TMP-195 or knockdown of HDAC5 and the blockade of the nuclear export of HDAC5 by leptomycin B or KPT-330 significantly reduced ANG II-induced Egr-1 expression. In addition, depletion of either HDAC5 or Egr-1 by siRNA attenuated VSMC hypertrophy in response to ANG II. In summary, our results demonstrate that ANG II-induced HDAC5 phosphorylation and its nuclear exclusion are mediated by PI3K/Akt pathway and HDAC5 is an upstream regulator of Egr-1 expression and hypertrophy in VSMCs.NEW & NOTEWORTHY ANG II-induced histone deacetylase 5 (HDAC5) phosphorylation and nuclear export occurs via the phosphoinositide 3-kinase/Akt pathway. Akt, through HDAC5, regulates ANG II-induced expression of early growth response protein-1 (Egr-1), which is a transcription factor linked with vascular dysfunction. Inhibition of HDAC5 exclusion by nuclear export inhibitors suppresses ANG II-induced Egr-1 expression. HDAC5 is an upstream mediator of Egr-1 expression and cell hypertrophy in response to ANG II in vascular smooth muscle cells.

Critical slowing down and attractive manifold: A mechanism for dynamic robustness in the yeast cell-cycle process.

Biological processes that execute complex multiple functions, such as the cell cycle, must ensure the order of sequential events and maintain dynamic robustness against various fluctuations. Here, we examine the mechanisms and fundamental structure that achieve these properties in the cell cycle of the budding yeast Saccharomyces cerevisiae. We show that this process behaves like an excitable system containing three well-decoupled saddle-node bifurcations to execute DNA replication and mitosis events. The yeast cell-cycle regulatory network can be divided into three modules-the G1/S phase, early M phase, and late M phase-wherein both positive feedback loops in each module and interactions among modules play important roles. Specifically, when the cell-cycle process operates near the critical points of the saddle-node bifurcations, a critical slowing down effect takes place. Such interregnum then allows for an attractive manifold and sufficient duration for cell-cycle events, within which to assess the completion of DNA replication and mitosis, e.g., spindle assembly. Moreover, such arrangement ensures that any fluctuation in an early module or event will not transmit to a later module or event. Thus, our results suggest a possible dynamical mechanism of the cell-cycle process to ensure event order and dynamic robustness and give insight into the evolution of eukaryotic cell-cycle processes.

Forkhead box M1 transcription factor: a novel target for pulmonary arterial hypertension therapy.

Forkhead box M1 (FoxM1), a member of forkhead family, plays a key role in carcinogenesis, progression, invasion, metastasis and drug resistance. Based on the similarities between cancer and pulmonary arterial hypertension, studies on the roles and mechanisms of FoxM1 in pulmonary arterial hypertension have been increasing. This article aims to review recent advances in the mechanisms of signal transduction associated with FoxM1 in pulmonary arterial hypertension. Articles were retrieved from PubMed and MEDLINE published after 1990, including-but not limited to-FoxM1 and pulmonary arterial hypertension. FoxM1 is overexpressed in pulmonary artery smooth muscle cells in both pulmonary arterial hypertension patients and animal models, and promotes pulmonary artery smooth muscle cell proliferation and inhibits cell apoptosis via regulating cell cycle progression. Multiple signaling molecules and pathways, including hypoxia-inducible factors, transforming growth factor-β/Smad, SET domain-containing 3/vascular endothelial growth factor, survivin, cell cycle regulatory genes and DNA damage response network, are reported to cross talk with FoxM1 in pulmonary arterial hypertension. Proteasome inhibitors are effective in the prevention and treatment of pulmonary arterial hypertension by inhibiting the expression and transcriptional activity of FoxM1. FoxM1 has a crucial role in the pathogenesis of pulmonary arterial hypertension and may represent a novel therapeutic target. But more details of interaction between FoxM1 and other signaling pathways need to be clarified in the future.

NRF2-regulated cell cycle arrest at early stage of oxidative stress response mechanism.

Oxidative stress results in activation of several signal transduction pathways controlled by the PERK-substrate NRF2 (nuclear factor erythroid 2-related factor 2); meanwhile the ongoing cell division cycle has to be blocked. It has been recently shown that Cyclin D1 got immediately down-regulated via PERK pathway in response to oxidative stress leading to cell cycle arrest. However, the effect of NRF2 on cell cycle regulation has not been explored yet. We aimed to reveal a crosstalk between PERK-substrate NRF2 and the key elements of cell cycle regulatory network upon oxidative stress using molecular biological techniques- Although Cyclin D1 level remained constant, its activity was blocked by various stoichiometric inhibitors (such as p15, p21 and p27) even at low level of oxidative stress. The activity of these CDK inhibitors completely disappeared, when the addition of oxidative agent was combined with silencing of either PERK or NRF2.This further confirms the important role of NRF2 in blocking Cyclin D1 with stoichiometric inhibitors at early stage of oxidative stress.

An agent-based model of the fission yeast cell cycle.

The objective of this paper is to develop a computational model of the fission yeast (Schizosaccharomyces pombe) cell cycle using agent-based modeling (ABM), to study the sequence of states of the proteins and time of the cell cycle phases, under the action of proteins that regulate its cell cycle. The model relies only on the conceptual model of the yeast cell cycle regulatory network, where each protein has been represented as an agent with a property called activity that represents its biological function and a stochastic Brownian movement. The results indicate that the simulated phase time did have similar results in comparison with other models using mathematical approaches. Similarly, the correct sequence of states was achieved, and the model was run under different initial states to understand its emergent behaviors. The cell reached the G1 stationary state 94% of the times when running the model under biological initial conditions and 87% of the times when running the model through all the different combinations of initial states. Such results imply that the cell was capable to fix toward the biological expected phenomena. These results show that ABM is a suitable technique to study protein-protein interactions without using, often unavailable, kinetic parameters, or differential equations. This model sets as a base for further studies that involve the cell cycle of the fission yeast, with a special attention to studies and development of drug treatments for specific types of cancer.

LncRNA PLAC2 down-regulates RPL36 expression and blocks cell cycle progression in glioma through a mechanism involving STAT1.

Current glioma therapies allow in situ delivery of cytotoxic drugs to the tumour; however, gliomas show early recurrence due to their highly proliferative character. Long non‐coding (lnc)RNAs play critical roles in tumorigenesis by controlling cell proliferation and cycling. However, the mechanism of action of lncRNAs in glioma development remains unclear. Here, we report that the lncRNA PLAC2 induces cell cycle arrest by targeting ribosomal protein (RP)L36 in glioma. RPL36 promoted cell proliferation and G1/S cell cycle progression. Mass spectrometry analysis revealed that signal transducer and activator of transcription (STAT)1 interacted with both lncRNA PLAC2 and the RPL36 promoter. We also found that the nucleus PLAC2 bind with STAT1 and interact with RPL36 promoters but the cytoplasmic lncRNA PLAC2 inhibited STAT1 nuclear transfer, thereby decreasing RP36 expression, inhibiting cell proliferation and inducing cell cycle arrest. These results provide evidence for a novel cell cycle regulatory network in glioma comprising the lncRNA PLAC2 along with STAT1 and RPL36 that can serve as a therapeutic target for glioma treatment.

Abstract 5547: A computational approach to predict tissue level cell cycle regulatory network for normal proliferating and cancer cells

Abstract Cell cycle control and regulation has been widely studied in terms of cyclin-dependent kinases (CDKs) activities, while only limited information are available on tissue contexts and signaling. In this study, we adopted a systems biology approach aiming to comprehensively capture how tissue level signaling events orchestrate cell cycle phases in a CDKs activities independent manner in both of normal and tumor tissues. We have applied our in house gene co-expression and bi-clustering analysis on a collection of 8 single cell transcriptomic sequencing datasets of normal proliferating human embryonic cells, 17 RNA-seq transcriptomic datasets of inflammatory tissues and 30 microarray data sets of chronic inflammatory diseases as normal proliferating reference and TCGA RNA-seq data for 20 cancer types aiming to identify cell cycle associated gene co-expression modules. Our results suggest that the tissue level signaling events are generally show distinct regulatory structures between tumor and normal tissues: 1) the Rho GTPase signaling pathways that control cell polarity, activate in G2/M transition phase in normal tissue, while mainly in G1 and S phases in tumor. 2) Focal adhesion kinases (FAK) drives G1/S transition in normal tissues, while activated in multiple phases in tumor. 3) Hippo signaling for cell size control activates at G2/M transition phase in normal tissue while in multiple phases in tumor. In addition, we have also generated tissue level regulatory networks for cell cycle controls by predicting possible collective effects of extra- and intra-cellular signaling for both normal proliferating and cancer cells. Citation Format: Tao Sheng, Sha Cao, Chi Zhang, Ying Xu. A computational approach to predict tissue level cell cycle regulatory network for normal proliferating and cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5547. doi:10.1158/1538-7445.AM2017-5547

Solving the influence maximization problem reveals regulatory organization of the yeast cell cycle.

The Influence Maximization Problem (IMP) aims to discover the set of nodes with the greatest influence on network dynamics. The problem has previously been applied in epidemiology and social network analysis. Here, we demonstrate the application to cell cycle regulatory network analysis for Saccharomyces cerevisiae. Fundamentally, gene regulation is linked to the flow of information. Therefore, our implementation of the IMP was framed as an information theoretic problem using network diffusion. Utilizing more than 26,000 regulatory edges from YeastMine, gene expression dynamics were encoded as edge weights using time lagged transfer entropy, a method for quantifying information transfer between variables. By picking a set of source nodes, a diffusion process covers a portion of the network. The size of the network cover relates to the influence of the source nodes. The set of nodes that maximizes influence is the solution to the IMP. By solving the IMP over different numbers of source nodes, an influence ranking on genes was produced. The influence ranking was compared to other metrics of network centrality. Although the top genes from each centrality ranking contained well-known cell cycle regulators, there was little agreement and no clear winner. However, it was found that influential genes tend to directly regulate or sit upstream of genes ranked by other centrality measures. The influential nodes act as critical sources of information flow, potentially having a large impact on the state of the network. Biological events that affect influential nodes and thereby affect information flow could have a strong effect on network dynamics, potentially leading to disease. Code and data can be found at: https://github.com/gibbsdavidl/miergolf.

Integration of TP53, DREAM, MMB-FOXM1 and RB-E2F target gene analyses identifies cell cycle gene regulatory networks.

Cell cycle (CC) and TP53 regulatory networks are frequently deregulated in cancer. While numerous genome-wide studies of TP53 and CC-regulated genes have been performed, significant variation between studies has made it difficult to assess regulation of any given gene of interest. To overcome the limitation of individual studies, we developed a meta-analysis approach to identify high confidence target genes that reflect their frequency of identification in independent datasets. Gene regulatory networks were generated by comparing differential expression of TP53 and CC-regulated genes with chromatin immunoprecipitation studies for TP53, RB1, E2F, DREAM, B-MYB, FOXM1 and MuvB. RNA-seq data from p21-null cells revealed that gene downregulation by TP53 generally requires p21 (CDKN1A). Genes downregulated by TP53 were also identified as CC genes bound by the DREAM complex. The transcription factors RB, E2F1 and E2F7 bind to a subset of DREAM target genes that function in G1/S of the CC while B-MYB, FOXM1 and MuvB control G2/M gene expression. Our approach yields high confidence ranked target gene maps for TP53, DREAM, MMB-FOXM1 and RB-E2F and enables prediction and distinction of CC regulation. A web-based atlas at www.targetgenereg.org enables assessing the regulation of any human gene of interest.

Concise Review: Control of Cell Fate Through Cell Cycle and Pluripotency Networks.

Pluripotent stem cells (PSCs) proliferate rapidly with a characteristic cell cycle structure consisting of short G1- and G2-gap phases. This applies broadly to PSCs of peri-implantation stage embryos, cultures of embryonic stem cells, induced pluripotent stem cells, and embryonal carcinoma cells. During the early stages of PSC differentiation however, cell division times increase as a consequence of cell cycle remodeling. Most notably, this is indicated by elongation of the G1-phase. Observations linking changes in the cell cycle with exit from pluripotency have raised questions about the role of cell cycle control in maintenance of the pluripotent state. Until recently however, this has been a difficult question to address because of limitations associated with experimental tools. Recent studies now show that pluripotency and cell cycle regulatory networks are intertwined and that cell cycle control mechanisms are an integral, mechanistic part of the PSC state. Studies in embryonal carcinoma, some 30 years ago, first suggested that pluripotent cells initiate differentiation when in the G1-phase. More recently, a molecular "priming" mechanism has been proposed to explain these observations in human embryonic stem cells. Complexity in this area has been increased by the realization that pluripotent cells exist in multiple developmental states and that in addition to each having their own characteristic gene expression and epigenetic signatures, they potentially have alternate modes of cell cycle regulation. This review will summarize current knowledge in these areas and will highlight important aspects of interconnections between the cell cycle, self-renewal, pluripotency, and cell fate decisions. Stem Cells 2016;34:1427-1436.

New scaling relation for information transfer in biological networks.

We quantify characteristics of the informational architecture of two representative biological networks: the Boolean network model for the cell-cycle regulatory network of the fission yeast Schizosaccharomyces pombe (Davidich et al. 2008 PLoS ONE 3, e1672 (doi:10.1371/journal.pone.0001672)) and that of the budding yeast Saccharomyces cerevisiae (Li et al. 2004 Proc. Natl Acad. Sci. USA 101, 4781-4786 (doi:10.1073/pnas.0305937101)). We compare our results for these biological networks with the same analysis performed on ensembles of two different types of random networks: Erdös-Rényi and scale-free. We show that both biological networks share features in common that are not shared by either random network ensemble. In particular, the biological networks in our study process more information than the random networks on average. Both biological networks also exhibit a scaling relation in information transferred between nodes that distinguishes them from random, where the biological networks stand out as distinct even when compared with random networks that share important topological properties, such as degree distribution, with the biological network. We show that the most biologically distinct regime of this scaling relation is associated with a subset of control nodes that regulate the dynamics and function of each respective biological network. Information processing in biological networks is therefore interpreted as an emergent property of topology (causal structure) and dynamics (function). Our results demonstrate quantitatively how the informational architecture of biologically evolved networks can distinguish them from other classes of network architecture that do not share the same informational properties.

Coherent regulation in yeast’s cell-cycle network

We define a measure of coherent activity for gene regulatory networks, a property that reflects the unity of purpose between the regulatory agents with a common target. We propose that such harmonious regulatory action is desirable under a demand for energy efficiency and may be selected for under evolutionary pressures. We consider two recent models of the cell-cycle regulatory network of the yeast, Saccharomyces cerevisiae as a case study and calculate their degree of coherence. A comparison with random networks of similar size and composition reveals that the yeast’s cell-cycle regulation is wired to yield an exceptionally high level of coherent regulatory activity. We also investigate the mean degree of coherence as a function of the network size, connectivity and the fraction of repressory/activatory interactions.