Intercellular Variability in Protein Levels from Stochastic Expression and Noisy Cell Cycle Processes

Expression of many genes varies as a cell transitions through different cell-cycle stages. How coupling between stochastic expression and cell cycle impacts cell-to-cell variability (noise) in the level of protein is not well understood. We analyse a model where a stable protein is synthesized in random bursts, and the frequency with which bursts occur varies within the cell cycle. Formulae quantifying the extent of fluctuations in the protein copy number are derived and decomposed into components arising from the cell cycle and stochastic processes. The latter stochastic component represents contributions from bursty expression and errors incurred during partitioning of molecules between daughter cells. These formulae reveal an interesting trade-off: cell-cycle dependencies that amplify the noise contribution from bursty expression also attenuate the contribution from partitioning errors. We investigate the existence of optimum strategies for coupling expression to the cell cycle that minimize the stochastic component. Intriguingly, results show that a zero production rate throughout the cell cycle, with expression only occurring just before cell division, minimizes noise from bursty expression for a fixed mean protein level. By contrast, the optimal strategy in the case of partitioning errors is to make the protein just after cell division. We provide examples of regulatory proteins that are expressed only towards the end of the cell cycle, and argue that such strategies enhance robustness of cell-cycle decisions to the intrinsic stochasticity of gene expression.

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Decomposing variability in protein levels from noisy expression, genome duplication and partitioning errors during cell-divisions

10.1101/026559 ◽

2015 ◽

Author(s):

Mohammad Soltani ◽

Cesar Augusto Vargas-Garcia ◽

Duarte Antunes ◽

Abhyudai Singh

Keyword(s):

Cell Cycle ◽

Cell Division ◽

Genome Duplication ◽

Gene Dosage ◽

Hybrid Approach ◽

Extrinsic Noise ◽

Protein Levels ◽

Copy Numbers ◽

Total Noise ◽

Stochastic Expression

Inside individual cells, expression of genes is inherently stochastic and manifests as cell-to-cell variability or noise in protein copy numbers. Since proteins half-lives can be comparable to the cell-cycle length, randomness in cell-division times generates additional intercellular variability in protein levels. Moreover, as many mRNA/protein species are expressed at low-copy numbers, errors incurred in partitioning of molecules between the mother and daughter cells are significant. We derive analytical formulas for the total noise in protein levels for a general class of cell-division time and partitioning error distributions. Using a novel hybrid approach the total noise is decomposed into components arising from i) stochastic expression; ii) partitioning errors at the time of cell-division and iii) random cell-division events. These formulas reveal that random cell-division times not only generate additional extrinsic noise but also critically affect the mean protein copy numbers and intrinsic noise components. Counter intuitively, in some parameter regimes noise in protein levels can decrease as cell-division times become more stochastic. Computations are extended to consider genome duplication, where the gene dosage is increased by two-fold at a random point in the cell-cycle. We systematically investigate how the timing of genome duplication influences different protein noise components. Intriguingly, results show that noise contribution from stochastic expression is minimized at an optimal genome duplication time. Our theoretical results motivate new experimental methods for decomposing protein noise levels from single-cell expression data. Characterizing the contributions of individual noise mechanisms will lead to precise estimates of gene expression parameters and techniques for altering stochasticity to change phenotype of individual cells.

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Systems Level Modeling of the Cell Cycle Using Budding Yeast

Cancer Informatics ◽

10.1177/117693510700300020 ◽

2007 ◽

Vol 3 ◽

pp. 117693510700300 ◽

Cited By ~ 2

Author(s):

B.P. Ingalls ◽

B.P. Duncker ◽

D.R. Kim ◽

B.J. McConkey

Keyword(s):

Cell Cycle ◽

Budding Yeast ◽

Human Cancer ◽

Quality Data ◽

Cell Cycle Gene ◽

Mathematical Framework ◽

Gene Transcript ◽

Proteomics Data ◽

Yeast Saccharomyces Cerevisiae ◽

Protein Levels

Proteins involved in the regulation of the cell cycle are highly conserved across all eukaryotes, and so a relatively simple eukaryote such as yeast can provide insight into a variety of cell cycle perturbations including those that occur in human cancer. To date, the budding yeast Saccharomyces cerevisiae has provided the largest amount of experimental and modeling data on the progression of the cell cycle, making it a logical choice for in-depth studies of this process. Moreover, the advent of methods for collection of high-throughput genome, transcriptome, and proteome data has provided a means to collect and precisely quantify simultaneous cell cycle gene transcript and protein levels, permitting modeling of the cell cycle on the systems level. With the appropriate mathematical framework and sufficient and accurate data on cell cycle components, it should be possible to create a model of the cell cycle that not only effectively describes its operation, but can also predict responses to perturbations such as variation in protein levels and responses to external stimuli including targeted inhibition by drugs. In this review, we summarize existing data on the yeast cell cycle, proteomics technologies for quantifying cell cycle proteins, and the mathematical frameworks that can integrate this data into representative and effective models. Systems level modeling of the cell cycle will require the integration of high-quality data with the appropriate mathematical framework, which can currently be attained through the combination of dynamic modeling based on proteomics data and using yeast as a model organism.

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Blockage of Potassium Channel Inhibits Proliferation of Glioma Cells Via Increasing Reactive Oxygen Species

Oncology Research Featuring Preclinical and Clinical Cancer Therapeutics ◽

10.3727/096504014x14098532393518 ◽

2014 ◽

Vol 22 (1) ◽

pp. 57-65 ◽

Cited By ~ 1

Author(s):

Li Hu ◽

Li-Li Li ◽

Zhi-Guo Lin ◽

Zhi-Chao Jiang ◽

Hong-Xing Li ◽

...

Keyword(s):

Reactive Oxygen Species ◽

Cell Cycle ◽

Glioma Cell ◽

Glioma Cells ◽

Reactive Oxygen ◽

Dependent Manner ◽

Oxygen Species ◽

Brain Glioma ◽

Protein Levels ◽

Glioma Cell Proliferation

The potassium (K+) channel plays an important role in the cell cycle and proliferation of tumor cells, while its role in brain glioma cells and the signaling pathways remains unclear. We used tetraethylammonium (TEA), a nonselective antagonist of big conductance K+ channels, to block K+ channels in glioma cells, and antioxidant N-acetyl-l-cysteine (NAC) to inhibit production of intracellular reactive oxygen species (ROS). TEA showed an antiproliferation effect on C6 and U87 glioma cells in a time-dependent manner, which was accompanied by an increased intracellular ROS level. Antioxidant NAC pretreatment reversed TEA-mediated antiproliferation and restored ROS level. TEA treatment also caused significant increases in mRNA and protein levels of tumor-suppressor proteins p53 and p21, and the upregulation was attenuated by pretreatment of NAC. Our results suggest that K+ channel activity significantly contributes to brain glioma cell proliferation via increasing ROS, and it might be an upstream factor triggering the activation of the p53/p21Cip1-dependent signaling pathway, consequently leading to glioma cell cycle arrest.

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The Saccharomyces cerevisiae YAK1 gene encodes a protein kinase that is induced by arrest early in the cell cycle.

Molecular and Cellular Biology ◽

10.1128/mcb.11.8.4045 ◽

1991 ◽

Vol 11 (8) ◽

pp. 4045-4052 ◽

Cited By ~ 86

Author(s):

S Garrett ◽

M M Menold ◽

J R Broach

Keyword(s):

Cell Cycle ◽

Protein Kinase ◽

Kinase Activity ◽

Specific Activity ◽

S Phase ◽

Protein Kinase Activity ◽

Dependent Protein Kinase ◽

Protein Levels ◽

Cycle Arrest ◽

Dependent Protein

Null mutations in the gene YAK1, which encodes a protein with sequence homology to known protein kinases, suppress the cell cycle arrest phenotype of mutants lacking the cyclic AMP-dependent protein kinase (A kinase). That is, loss of the YAK1 protein specifically compensates for loss of the A kinase. Here, we show that the protein encoded by YAK1 has protein kinase activity. Yak1 kinase activity is low during exponential growth but is induced at least 50-fold by arrest of cells prior to the completion of S phase. Induction is not observed by arrest at stages later in the cell cycle. Depending on the arrest regimen, induction can occur either by an increase in Yak1 protein levels or by an increase in Yak1 specific activity. Finally, an increase in Yak1 protein levels causes growth arrest of cells with attenuated A kinase activity. These results suggest that Yak1 acts in a pathway parallel to that of the A kinase to negatively regulate cell proliferation.

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The transcription factors TFE3 and TFEB amplify p53 dependent transcriptional programs in response to DNA damage

eLife ◽

10.7554/elife.40856 ◽

2018 ◽

Vol 7 ◽

Cited By ~ 15

Author(s):

Eutteum Jeong ◽

Owen A Brady ◽

José A Martina ◽

Mehdi Pirooznia ◽

Ilker Tunc ◽

...

Keyword(s):

Cell Cycle ◽

Dna Damage ◽

Transcription Factors ◽

P53 Protein ◽

Cell Cycle Control ◽

Cell Cycle Checkpoints ◽

Dependent Manner ◽

Double Knockout ◽

Protein Levels ◽

Regulation Of Cell Cycle

The transcription factors TFE3 and TFEB cooperate to regulate autophagy induction and lysosome biogenesis in response to starvation. Here we demonstrate that DNA damage activates TFE3 and TFEB in a p53 and mTORC1 dependent manner. RNA-Seq analysis of TFEB/TFE3 double-knockout cells exposed to etoposide reveals a profound dysregulation of the DNA damage response, including upstream regulators and downstream p53 targets. TFE3 and TFEB contribute to sustain p53-dependent response by stabilizing p53 protein levels. In TFEB/TFE3 DKOs, p53 half-life is significantly decreased due to elevated Mdm2 levels. Transcriptional profiles of genes involved in lysosome membrane permeabilization and cell death pathways are dysregulated in TFEB/TFE3-depleted cells. Consequently, prolonged DNA damage results in impaired LMP and apoptosis induction. Finally, expression of multiple genes implicated in cell cycle control is altered in TFEB/TFE3 DKOs, revealing a previously unrecognized role of TFEB and TFE3 in the regulation of cell cycle checkpoints in response to stress.

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Aurora kinases A and B are up-regulated by Myc and are essential for maintenance of the malignant state

Blood ◽

10.1182/blood-2009-11-251074 ◽

2010 ◽

Vol 116 (9) ◽

pp. 1498-1505 ◽

Cited By ~ 140

Author(s):

Jürgen den Hollander ◽

Sara Rimpi ◽

Joanne R. Doherty ◽

Martina Rudelius ◽

Andreas Buck ◽

...

Keyword(s):

Cell Cycle ◽

Kinase Activity ◽

Kinase Inhibitor ◽

Aurora Kinase ◽

Cell Cycle Regulators ◽

Aurora Kinase Inhibitor ◽

Aurora Kinases ◽

Protein Levels ◽

Malignant State ◽

E Boxes

Myc oncoproteins promote continuous cell growth, in part by controlling the transcription of key cell cycle regulators. Here, we report that c-Myc regulates the expression of Aurora A and B kinases (Aurka and Aurkb), and that Aurka and Aurkb transcripts and protein levels are highly elevated in Myc-driven B-cell lymphomas in both mice and humans. The induction of Aurka by Myc is transcriptional and is directly mediated via E-boxes, whereas Aurkb is regulated indirectly. Blocking Aurka/b kinase activity with a selective Aurora kinase inhibitor triggers transient mitotic arrest, polyploidization, and apoptosis of Myc-induced lymphomas. These phenotypes are selectively bypassed by a kinase inhibitor-resistant Aurkb mutant, demonstrating that Aurkb is the primary therapeutic target in the context of Myc. Importantly, apoptosis provoked by Aurk inhibition was p53 independent, suggesting that Aurka/Aurkb inhibitors will show efficacy in treating primary or relapsed malignancies having Myc involvement and/or loss of p53 function.

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Upregulation of SGOL2 Predicts Poor Prognosis and Facilitates Hepatocellular Carcinoma Progression via Dysregulating the Cell Cycle by Directly Activating MAD2

10.21203/rs.3.rs-560609/v1 ◽

2021 ◽

Author(s):

Qingqing Hu ◽

Xiaochu Hu ◽

Yalei Zhao ◽

Lingjian Zhang ◽

Ya Yang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Cell Cycle ◽

The Cancer Genome Atlas ◽

Loss Of Function ◽

Protein Levels ◽

Cancer Genome Atlas ◽

Centromeric Protein ◽

Hcc Cells

Abstract Background: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide. Shugoshin-like protein 2 (SGOL2) is a centromeric protein that ensures the correct and orderly process of mitosis by protecting and maintaining centripetal adhesions during meiosis and mitosis. However, the role of SGOL2 in cancer is not well understood. Methods: The mRNA and protein levels of SGOL2 and survival analysis were conducted in The Cancer Genome Atlas (TCGA) and further validated in 2 independent cohorts. Differential genes correlated with SGOL2 and mitotic arrest deficient 2 like 1 (MAD2) were obtained using LinkedOmics. Subsequently, loss-of-function and rescue assays were carried out in vitro and in vivo to assess the functions of SGOL2 in hepatic tumorigenisis. Findings: We found that SGOL2 was significantly overexpressed in HCC and predicted unfavorable overall survival in HCC patients. Next, we identified 47 differentially expressed genes positively correlated with both SGOL2 and MAD2 to be mainly involved in the cell cycle. In addition, SGOL2 downregulation suppressed the migration, invasion, proliferation, stemness and EMT of HCC cells and inhibited tumorigenesis in vivo. Furthermore, SGOL2 promoted tumor proliferation by activating MAD2-induced cell cycle dysregulation, which could be reversed by the MAD2 inhibitor M2I-1. We also proved that SGOL2 activated MAD2 by directly binding with MAD2. Conclusions: The results of this study showed that SGOL2 acts as an oncogene in HCC cells by directly activating MAD2 and then dysregulating the cell cycle, thereby providing a potential target for HCC patients in the future.

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Cleavage and polyadenylation-specific factor 3 induces cell cycle arrest via PI3K/Akt/GSK-3β signaling pathways and predicts a negative prognosis in hepatocellular carcinoma

Biomarkers in Medicine ◽

10.2217/bmm-2021-0039 ◽

2021 ◽

Vol 15 (5) ◽

pp. 347-358

Author(s):

Ning Li ◽

Shaotao Jiang ◽

Rongdang Fu ◽

Jin Lv ◽

Jiyou Yao ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Cell Cycle ◽

Cell Lines ◽

Potential Role ◽

Control Group ◽

Specific Factor ◽

Protein Levels ◽

Cycle Arrest ◽

Cleavage And Polyadenylation ◽

Gsk 3Β

Background: Recent studies have shown that cleavage and polyadenylation-specific factor 3 (CPSF3) is a promising antitumor therapeutic target, but its potential role in hepatocellular carcinoma (HCC) has not been reported. Materials & methods: We explored the expression pattern of CPSF3 in HCC through bioinformatics analysis, quantitative polymerase chain reaction (qPCR) and western blot. The potential role of CPSF3 as a biomarker for HCC was evaluated by Kaplan–Meier analysis. Next, changes in HCC cell lines in the CPSF3 knockdown model group and the control group were assessed by Cell Counting Kit-8, clonal formation, flow cytometry and EdU staining. Western blot detected changes in protein levels of the PI3K/Akt/GSK-3β axis of two HCC cell lines in the knockdown group and the control group. Results: The results showed that the transcription and protein levels of CPSF3 were significantly higher in HCC tissues than in adjacent normal tissues (p < 0.05). The HCC cohort with increased expression of CPSF3 is associated with advanced stage and differentiation and predicts poorer prognosis (p < 0.05). CPSF3 knockdown significantly inhibited proliferation and clone formation of HepG2 and SMMC-7721 cell lines. Flow cytometry analysis showed G1–S cell cycle arrest in the CPSF3 knockdown group, and the results of EdU staining were consistent with this. Compared with the control group, p-Akt and cyclin D1 were decreased, and GSK-3β was increased in the knockdown group. Conclusion: CPSF3 may be a potential diagnostic biomarker and candidate therapeutic target for HCC.

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Starvation promotes Dictyostelium development by relieving PufA inhibition of PKA translation through the YakA kinase pathway

Development ◽

10.1242/dev.126.14.3263 ◽

1999 ◽

Vol 126 (14) ◽

pp. 3263-3274 ◽

Cited By ~ 3

Author(s):

G.M. Souza ◽

A.M. da Silva ◽

A. Kuspa

Keyword(s):

Cell Cycle ◽

Protein Kinase ◽

Mrna Levels ◽

Wild Type ◽

Mobility Shift ◽

Developmental Defects ◽

C Protein ◽

Protein Levels ◽

Cell Extracts ◽

Puf Protein

When nutrients are depleted, Dictyostelium cells undergo cell cycle arrest and initiate a developmental program that ensures survival. The YakA protein kinase governs this transition by regulating the cell cycle, repressing growth-phase genes and inducing developmental genes. YakA mutants have a shortened cell cycle and do not initiate development. A suppressor of yakA that reverses most of the developmental defects of yakA- cells, but none of their growth defects was identified. The inactivated gene, pufA, encodes a member of the Puf protein family of translational regulators. Upon starvation, pufA- cells develop precociously and overexpress developmentally important proteins, including the catalytic subunit of cAMP-dependent protein kinase, PKA-C. Gel mobility-shift assays using a 200-base segment of PKA-C's mRNA as a probe reveals a complex with wild-type cell extracts, but not with pufA- cell extracts, suggesting the presence of a potential PufA recognition element in the PKA-C mRNA. PKA-C protein levels are low at the times of development when this complex is detectable, whereas when the complex is undetectable PKA-C levels are high. There is also an inverse relationship between PufA and PKA-C protein levels at all times of development in every mutant tested. Furthermore, expression of the putative PufA recognition elements in wild-type cells causes precocious aggregation and PKA-C overexpression, phenocopying a pufA mutation. Finally, YakA function is required for the decline of PufA protein and mRNA levels in the first 4 hours of development. We propose that PufA is a translational regulator that directly controls PKA-C synthesis and that YakA regulates the initiation of development by inhibiting the expression of PufA. Our work also suggests that Puf protein translational regulation evolved prior to the radiation of metazoan species.

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