On chaotic dynamics in transcription factors and the associated effects in differential gene regulation

Heltberg, Mathias L.; Krishna, Sandeep; Jensen, Mogens H.

doi:10.1038/s41467-018-07932-1

Cited by 76 publications

(76 citation statements)

References 42 publications

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“…Furthermore, it was recently confirmed the chaotic dynamics in the transcription factor NF-κB, a welldescribed transcriptional regulator in cancer networks, can affect downstream protein production (51). The nonlinear genetic oscillator NF-κB, when periodically driven by sufficiently large TNF (tumor necrosis factor) amplitudes, will exhibit deterministic chaos.…”

Section: Symmetry-breakingmentioning

confidence: 90%

Cancer: A Turbulence Problem

Uthamacumaran

2019

Preprint

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As we transition towards an era of Computational Medicine, our mathematical models of cancer dynamics must be revised. As such, recent evidence supports the perspective that cancermicroenvironment interactions consist of turbulent flows and strange attractor dynamics. Cancer pattern formation, invasion-growth dynamics, protein folding kinetics, stem cell fate bifurcations and metastatic invasion are discussed within the context of hydrodynamical turbulence. Cancer is presented as a three-dimensional Navier-Stokes equations global regularity, smoothness and existence problem. POSTULATE:Cancer stem cells are strange attractors on the Waddington energy landscape governed by turbulence dynamics. EMERGENCECancers are complex systems. The Hanahan-Weinberg 'hallmarks' are an inadequate representation of these dynamical systems. Complex systems are systems in which the interactions of its elements and parts cannot be deduced due to interdependence. Some general characteristics of complex systems include nonlinearity, emergence, computational irreducibility, unpredictability, nonequilibrium statistical mechanics and intractability. In simple terms, the concerted whole cannot be defined by the sum of its interacting parts. For example, the flow of exosomes between cancer cells are emergent characteristics of tumor ecosystems. It is impossible to understand exosomes without complex systems approaches. Exosomes are heterogeneous nano-scaled packets of information forming complex long-range communication networks. Along with ctDNA (circulating tumor DNA), exosomes are emerging targets for early tumor detection from liquid biopsies of patients (1, 2). Human embryonic stem cells-derived exosomes have shown capability of reprogramming malignant cancer phenotypes to benign-like fates, indicating exosomes are potent phenotype reprogramming machineries (3). However, the identity of cancer stem cells remains ambiguous. It is debated whether cancer stem cells conform a small subset of the tumor hierarchy or whether all cancer cells are potentially stem cells (i.e., have the potency of phenotypic plasticity and unlimited replication). In attempt to reconcile such problems, precision oncology is transitioning towards the use of artificial intelligence and machine learning algorithms in guiding clinical decision-making (4). Machine intelligence is emerging as a powerful tool in deciphering cancer ecosystems.Each tumor exhibits spatio-temporal heterogeneity and emergent properties that are unpredictable. For example, certain malignant melanomas spontaneously regress, a property not recognized as a hallmark (5). Another example, PEDF (pigment epithelium-derived factor) upregulated by extracellular vesicle bodies-mediated EGFRvIII promotes the self-renewal and propagation of GSCs (glioma stem cells) (6, 7). However, PEDF is an anti-angiogenic factor and GSCs require vascular interactions for development. Such complex feedback loops are emergent properties of complex systems. Certain tumors exhibit vasculogenic mimicry, the spontaneous form...

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Section: Symmetry-breakingmentioning

confidence: 90%

Cancer: A Turbulence Problem

Uthamacumaran

2019

Preprint

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“…Our results are in agreement with previous work and complement this work. For example, experimental evidence suggests that the affinity of essential regulators of gene expression, such as NF-κB and TBP, modulates gene expression noise (50,51). Moreover, a model based on the binding dynamics of Sox2 and Oct4, two important regulators of the pluripotency of stems cells, showed that long residence times reduce the sensitivity of gene expression to TF concentration, because TFs with long residence times are bound to DNA most of the time regardless of their concentration (26,31).…”

Section: Discussionmentioning

confidence: 99%

Short residence times of DNA-bound transcription factors can reduce gene expression noise and increase the transmission of information in a gene regulation system

Azpeitia

Wagner

2019

Preprint

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AbstractGene expression noise is not just ubiquitous but also variable, and we still do not understand some of the most elementary factors that affect it. Among them is the residence time of a transcription factor (TF) on DNA, the mean time that a DNA-bound TF remains bound. Here, we use a stochastic model of transcriptional regulation to study how this residence time affects gene expression. We find that the effect of residence time on gene expression depends on the level of induction of the gene. At high levels of induction, residence time has no effect on gene expression. However, as the level of induction decreases, short residence times reduce gene expression noise. The reason is that fast on-off TF binding dynamics prevent long periods where proteins are predominantly synthesized or degraded, which can cause excessive fluctuations in gene expression. As a consequence, short residence times can help a gene regulation system acquire information about the cellular environment it operates in. Our predictions are consistent with the observation that experimentally measured residence times are usually modest and lie between seconds to minutes.

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“…However, it can be inferred that the endothelial response could be significant and probably chaotic, which determine transcription and gene regulation. 73 Chaos does not necessarily lead to dysfunctions, and at times and situations, it could be a natural method of selection to strengthen immune functions. Optical laser chaos signals which are high speed when studied are found to synchronize and it has many features.…”

Section: Chaos and Decodingmentioning

confidence: 99%

A Novel Method of Immunomodulation of Endothelial cells Using Streptococcus Pyogenes and its Lysate

Arokiaraj

Wilson

2020

Preprint

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Background:Coronary artery diseases and autoimmune disorders are common in clinical practice. In this study, a novel method of immune-modulation to modify the endothelial function was studied to modulate the features of the endothelial cells, and thereby to reduce coronary artery disease and other disorders modulated by endothelium. Methods:HUVEC cells were seeded in the cell culture, and streptococcus pyogenes were added to the cell culture, and the supernatant was studied for the secreted proteins. In the second phase, the bacterial lysate was synthesized, and the lysate was added to cell culture; and the proteins in the supernatant were studied at various time intervals. Results:When streptococcus pyogenes alone was added to culture, E Cadherin, Angiostatin, EpCAM and PDGF-AB were some of the biomarkers elevated significantly. HCC1, IGFBP2 and TIMP were some of the biomarkers which showed a reduction. When the lysate was added, the cell-culture was maintained for a longer time, and it showed the synthesis of immune regulatory cytokines. Heatmap analysis showed a significant number of proteins/cytokines concerning the immune/pathways, and toll-like receptors superfamily were modified. BLC, IL 17, BMP 7, PARC, Contactin2, IL 10 Rb, NAP 2 (CXCL 7), Eotaxin 2 were maximally increased. By principal component analysis, the results observed were significant. Conclusion:There is potential for a novel method of immunomodulation of the endothelial cells, which have pleiotropic functions, using streptococcus pyogenes and its lysates.

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On chaotic dynamics in transcription factors and the associated effects in differential gene regulation

Cited by 76 publications

References 42 publications

Cancer: A Turbulence Problem

Cancer: A Turbulence Problem

Short residence times of DNA-bound transcription factors can reduce gene expression noise and increase the transmission of information in a gene regulation system

A Novel Method of Immunomodulation of Endothelial cells Using Streptococcus Pyogenes and its Lysate

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