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Stochastic gene regulation

Sudip Nepal, Pradeep Kumar
Phenotypic switching is one of the mechanisms by which bacteria thrive in ever changing environmental conditions around them. Earlier studies have shown that the application of steady high hydrostatic pressure leads to stochastic switching of mesophilic bacteria from a cellular phenotype having a normal cell cycle to another phenotype lacking cell division. Here, we have studied the dynamics of this phenotypic switching with fluctuating periodic pressure using a set of experiments and a theoretical model. Our results suggest that the phenotypic switching rate from high-pressure phenotype to low-pressure phenotype in the reversible regime is larger as compared to the switching rate from low-pressure phenotype to high-pressure phenotype...
May 2018: Physical Review. E
Niraj Kumar, Kourosh Zarringhalam, Rahul V Kulkarni
Noncoding small RNAs (sRNAs) are known to play a key role in regulating diverse cellular processes, and their dysregulation is linked to various diseases such as cancer. Such diseases are also marked by phenotypic heterogeneity, which is often driven by the intrinsic stochasticity of gene expression. Correspondingly, there is significant interest in developing quantitative models focusing on the interplay between stochastic gene expression and regulation by sRNAs. We consider the canonical model of regulation of stochastic gene expression by sRNAs, wherein interaction between constitutively expressed sRNAs and mRNAs leads to stoichiometric mutual degradation...
June 5, 2018: Biophysical Journal
M Son, J Kaspar, S J Ahn, R A Burne, S J Hagen
Many bacterial species use the MecA/ClpCP proteolytic system to block entry into genetic competence. In Streptococcus mutans, MecA/ClpCP degrades ComX (also called SigX), an alternative sigma factor for the comY operon and other late competence genes. Although the mechanism of MecA/ClpCP has been studied in multiple Streptococcus species, its role within noisy competence pathways is poorly understood. S. mutans competence can be triggered by two different peptides, CSP and XIP, but it is not known whether MecA/ClpCP acts similarly for both stimuli, how it affects competence heterogeneity, and how its regulation is overcome...
June 5, 2018: Molecular Microbiology
Cesar A Vargas-Garcia, Khem Raj Ghusinga, Abhyudai Singh
Growth of a cell and its subsequent division into daughters is a fundamental aspect of all cellular living systems. During these processes, how do individual cells correct size aberrations so that they do not grow abnormally large or small? How do cells ensure that the concentration of essential gene products are maintained at desired levels, in spite of dynamic/stochastic changes in cell size during growth and division? Both these questions have fascinated researchers for over a century. We review how advances in singe-cell technologies and measurements are providing unique insights into these questions across organisms from prokaryotes to human cells...
April 2018: Current Opinion in Systems Biology
Stuart A Sevier, Herbert Levine
In recent years, physical elements of transcription have emerged as central in our understanding of gene expression. Recent work has been done introducing a simple description of the basic physical elements of transcription where RNA elongation, RNA polymerase (RNAP) rotation and DNA supercoiling are coupled (1). Here we generalize this framework to accommodate the behavior of many RNAPs operating on multiple genes on a shared piece of DNA. The resulting framework is combined with well-established stochastic processes of transcription resulting in a model which characterizes the impact of the mechanical properties of transcription on gene expression and DNA structure...
June 1, 2018: Nucleic Acids Research
Aouefa Amoussouvi, Lotte Teufel, Matthias Reis, Martin Seeger, Julia Katharina Schlichting, Gabriele Schreiber, Andreas Herrmann, Edda Klipp
Gene expression is a stochastic process and its appropriate regulation is critical for cell cycle progression. Cellular stress response necessitates expression reprogramming and cell cycle arrest. While previous studies are mostly based on bulk experiments influenced by synchronization effects or lack temporal distribution, time-resolved methods on single cells are needed to understand eukaryotic cell cycle in context of noisy gene expression and external perturbations. Using smFISH, microscopy and morphological markers, we monitored mRNA abundances over cell cycle phases and calculated transcriptional noise for SIC1 , CLN2 , and CLB5 , the main G1/S transition regulators in budding yeast...
2018: NPJ Systems Biology and Applications
Akinori Awazu, Takahiro Tanabe, Mari Kamitani, Ayumi Tezuka, Atsushi J Nagano
Gene expression levels exhibit stochastic variations among genetically identical organisms under the same environmental conditions. In many recent transcriptome analyses based on RNA sequencing (RNA-seq), variations in gene expression levels among replicates were assumed to follow a negative binomial distribution, although the physiological basis of this assumption remains unclear. In this study, RNA-seq data were obtained from Arabidopsis thaliana under eight conditions (21-27 replicates), and the characteristics of gene-dependent empirical probability density function (ePDF) profiles of gene expression levels were analyzed...
May 29, 2018: Scientific Reports
Rebecca A Zabinsky, Grace Alexandria Mason, Christine Queitsch, Daniel F Jarosz
Canalization, or phenotypic robustness in the face of environmental and genetic perturbation, is an emergent property of living systems. Although this phenomenon has long been recognized, its molecular underpinnings have remained enigmatic until recently. Here, we review the contributions of the molecular chaperone Hsp90, a protein that facilitates the folding of many key regulators of growth and development, to canalization of phenotype - and de-canalization in times of stress - drawing on studies in eukaryotes as diverse as baker's yeast, mouse ear cress, and blind Mexican cavefish...
May 25, 2018: Seminars in Cell & Developmental Biology
Daniel Onofre Vidal, Anelisa Ramão, Daniel Guariz Pinheiro, Bruna Rodrigues Muys, Julio Cesar Cetrulo Lorenzi, Cleidson de Pádua Alves, Dalila Luciola Zanette, Greice Andreotti de Molfetta, Geraldo Duarte, Wilson Araújo Silva
Despite being a healthy tissue, the constituent cells of the placenta, share similar characteristics with tumor cells, such as increased cell growth, migration, and invasion. However, while these processes are stochastic and uncontrolled in cancer cells, in placenta they are precisely controlled. Since miRNAs have been reported to regulate genes that control the molecular mechanisms necessary for the development of both human placenta and cancer, we addressed for miRNAs highly expressed in the placenta that could be involved in tumorigenesis...
May 4, 2018: Oncotarget
Peter Czuppon, Peter Pfaffelhuber
Gene expression is influenced by extrinsic noise (involving a fluctuating environment of cellular processes) and intrinsic noise (referring to fluctuations within a cell under constant environment). We study the standard model of gene expression including an (in-)active gene, mRNA and protein. Gene expression is regulated in the sense that the protein feeds back and either represses (negative feedback) or enhances (positive feedback) its production at the stage of transcription. While it is well-known that negative (positive) feedback reduces (increases) intrinsic noise, we give a precise result on the resulting fluctuations in protein numbers...
May 24, 2018: Journal of Mathematical Biology
Mark Grimes, Benjamin Hall, Lauren Foltz, Tyler Levy, Klarisa Rikova, Jeremiah Gaiser, William Cook, Ekaterina Smirnova, Travis Wheeler, Neil R Clark, Alexander Lachmann, Bin Zhang, Peter Hornbeck, Avi Ma'ayan, Michael Comb
Protein posttranslational modifications (PTMs) have typically been studied independently, yet many proteins are modified by more than one PTM type, and cell signaling pathways somehow integrate this information. We coupled immunoprecipitation using PTM-specific antibodies with tandem mass tag (TMT) mass spectrometry to simultaneously examine phosphorylation, methylation, and acetylation in 45 lung cancer cell lines compared to normal lung tissue and to cell lines treated with anticancer drugs. This simultaneous, large-scale, integrative analysis of these PTMs using a cluster-filtered network (CFN) approach revealed that cell signaling pathways were outlined by clustering patterns in PTMs...
May 22, 2018: Science Signaling
David J Jörg, Luis G Morelli, Frank Jülicher
We introduce a stochastic model of coupled genetic oscillators in which chains of chemical events involved in gene regulation and expression are represented as sequences of Poisson processes. We characterize steady states by their frequency, their quality factor, and their synchrony by the oscillator cross correlation. The steady state is determined by coupling and exhibits stochastic transitions between different modes. The interplay of stochasticity and nonlinearity leads to isolated regions in parameter space in which the coupled system works best as a biological pacemaker...
March 2018: Physical Review. E
Guillermo Rodrigo
Gene expression programs in living cells are highly dynamic due to spatiotemporal molecular signaling and inherent biochemical stochasticity. Here we study a mechanism based on molecule-to-molecule variability at the RNA level for the generation of bursts of protein production, which can lead to heterogeneity in a cell population. We develop a mathematical framework to show numerically and analytically that genes regulated post transcriptionally by small RNA molecules can exhibit such bursts due to different states of translation activity (on or off), mostly revealed in a regime of few molecules...
March 2018: Physical Review. E
Marc Rullan, Dirk Benzinger, Gregor W Schmidt, Andreas Milias-Argeitis, Mustafa Khammash
Transcription is a highly regulated and inherently stochastic process. The complexity of signal transduction and gene regulation makes it challenging to analyze how the dynamic activity of transcriptional regulators affects stochastic transcription. By combining a fast-acting, photo-regulatable transcription factor with nascent RNA quantification in live cells and an experimental setup for precise spatiotemporal delivery of light inputs, we constructed a platform for the real-time, single-cell interrogation of transcription in Saccharomyces cerevisiae...
May 17, 2018: Molecular Cell
Sandeep Choubey, Jane Kondev, Alvaro Sanchez
Transcription is the dominant point of control of gene expression. Biochemical studies have revealed key molecular components of transcription and their interactions, but the dynamics of transcription initiation in cells is still poorly understood. This state of affairs is being remedied with experiments that observe transcriptional dynamics in single cells using fluorescent reporters. Quantitative information about transcription initiation dynamics can also be extracted from experiments that use electron micrographs of RNA polymerases caught in the act of transcribing a gene (Miller spreads)...
May 8, 2018: Biophysical Journal
Haitham A Shaban, Roman Barth, Kerstin Bystricky
Intrinsic dynamics of chromatin contribute to gene regulation. How chromatin mobility responds to genomic processes, and whether this response relies on coordinated chromatin movement is still unclear. Here, we introduce an approach called Dense Flow reConstruction and Correlation (DFCC), to quantify correlation of chromatin motion with sub-pixel sensitivity at the level of the whole nucleus. DFCC reconstructs dense global flow fields of fluorescent images acquired in real-time. We applied our approach to analyze stochastic movements of DNA and histones, based on direction and magnitude at different time lags in human cells...
April 30, 2018: Nucleic Acids Research
Claire S Simon, Anna-Katerina Hadjantonakis, Christian Schröter
Understanding how individual cells make fate decisions that lead to the faithful formation and homeostatic maintenance of tissues is a fundamental goal of contemporary developmental and stem cell biology. Seemingly uniform populations of stem cells and multipotent progenitors display a surprising degree of heterogeneity, primarily originating from the inherent stochastic nature of molecular processes underlying gene expression. Despite this heterogeneity, lineage decisions result in tissues of a defined size and with consistent proportions of differentiated cell types...
April 30, 2018: Wiley Interdisciplinary Reviews. Developmental Biology
Angel-Carlos Román, Julián Vicente-Page, Alfonso Pérez-Escudero, Jose M Carvajal-González, Pedro M Fernández-Salguero, Gonzalo G de Polavieja
BACKGROUND: Animals can show very different behaviors even in isogenic populations, but the underlying mechanisms to generate this variability remain elusive. We use the zebrafish (Danio rerio) as a model to test the influence of histone modifications on behavior. RESULTS: We find that laboratory and isogenic zebrafish larvae show consistent individual behaviors when swimming freely in identical wells or in reaction to stimuli. This behavioral inter-individual variability is reduced when we impair the histone deacetylation pathway...
April 25, 2018: Genome Biology
Stephen J Bush, Charity Muriuki, Mary E B McCulloch, Iseabail L Farquhar, Emily L Clark, David A Hume
BACKGROUND: mRNA-like long non-coding RNAs (lncRNAs) are a significant component of mammalian transcriptomes, although most are expressed only at low levels, with high tissue-specificity and/or at specific developmental stages. Thus, in many cases lncRNA detection by RNA-sequencing (RNA-seq) is compromised by stochastic sampling. To account for this and create a catalogue of ruminant lncRNAs, we compared de novo assembled lncRNAs derived from large RNA-seq datasets in transcriptional atlas projects for sheep and goats with previous lncRNAs assembled in cattle and human...
April 24, 2018: Genetics, Selection, Evolution: GSE
François Bertaux, Samuel Marguerat, Vahid Shahrezaei
The cell division rate, size and gene expression programmes change in response to external conditions. These global changes impact on average concentrations of biomolecule and their variability or noise. Gene expression is inherently stochastic, and noise levels of individual proteins depend on synthesis and degradation rates as well as on cell-cycle dynamics. We have modelled stochastic gene expression inside growing and dividing cells to study the effect of division rates on noise in mRNA and protein expression...
March 2018: Royal Society Open Science
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