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Stochastic gene regulation

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
Lisa Weber, William Raymond, Brian Munsky
In quantitative analyses of biological processes, one may use many different scales of models (e.g., spatial or non-spatial, deterministic or stochastic, time-varying or at steady-state) or many different approaches to match models to experimental data (e.g., model fitting or parameter uncertainty/sloppiness quantification with different experiment designs). These different analyses can lead to surprisingly different results, even when applied to the same data and the same model. We use a simplified gene regulation model to illustrate many of these concerns, especially for ODE analyses of deterministic processes, chemical master equation and finite state projection analyses of heterogeneous processes, and stochastic simulations...
April 6, 2018: Physical Biology
Peter L Freddolino, Jamie Yang, Amir Momen-Roknabadi, Saeed Tavazoie
Cells adapt to familiar changes in their environment by activating predefined regulatory programs that establish adaptive gene expression states. These hard-wired pathways, however, may be inadequate for adaptation to environments never encountered before. Here, we reveal evidence for an alternative mode of gene regulation that enables adaptation to adverse conditions without relying on external sensory information or genetically predetermined cis -regulation. Instead, individual genes achieve optimal expression levels through a stochastic search for improved fitness...
April 5, 2018: ELife
Kristen E Howery, Emrah Şimşek, Minsu Kim, Philip N Rather
Using a variety of techniques, we demonstrate the Class I regulator of the flagellar cascade, FlhD4 C2 , can activate its own expression in Proteus mirabilis. This activation was direct, as the FlhD4 C2 protein specifically bound to its promoter region. The expression of bacterial genes under a positive feedback control can exhibit varying levels between cells due to stochastic fluctuations that activate the feedback loop and result in some cells in an "ON" state. Cells containing a chromosomal flhDC::gfp transcriptional fusion exhibited a heterogeneous pattern of expression within the population during growth on agar surfaces and the percentage of cells expressing GFP increased as cells approached swarmer cell differentiation...
March 23, 2018: Research in Microbiology
Davar Abedini, Sajad Rashidi Monfared
A primary mechanism for controlling the development of multicellular organisms is transcriptional regulation, which carried out by transcription factors (TFs) that recognize and bind to their binding sites on promoter region. The distance from translation start site, order, orientation, and spacing between cis elements are key factors in the concentration of active nuclear TFs and transcriptional regulation of target genes. In this study, overrepresented motifs in cold and pathogenesis responsive genes were scanned via Gibbs sampling method, this method is based on detection of overrepresented motifs by means of a stochastic optimization strategy that searches for all possible sets of short DNA segments...
March 17, 2018: Molecular Biology Reports
Sandeep Choubey
Regulation of transcription is a vital process in cells, but mechanistic details of this regulation still remain elusive. The dominant approach to unravel the dynamics of transcriptional regulation is to first develop mathematical models of transcription and then experimentally test the predictions these models make for the distribution of mRNA and protein molecules at the individual cell level. However, these measurements are affected by a multitude of downstream processes which make it difficult to interpret the measurements...
February 2018: Physical Review. E
Sigrun Schmähling, Arno Meiler, Yoonjung Lee, Arif Mohammed, Katja Finkl, Katharina Tauscher, Lars Israel, Marc Borath, Julia Philippou-Massier, Helmut Blum, Bianca Habermann, Axel Imhof, Ji-Joon Song, Jürg Müller
The Drosophila Ash1 protein is a trithorax-group (trxG) regulator that antagonizes Polycomb repression at HOX genes. Ash1 di-methylates lysine 36 in histone H3 (H3K36me2) but how this activity is controlled and at which genes it functions is not well understood. We show that Ash1 protein purified from Drosophila exists in a complex with MRG15 and Caf1 that we named AMC. In Drosophila and human AMC, MRG15 binds a conserved FxLP motif near the Ash1 SET domain and stimulates H3K36 di-methylation on nucleosomes...
March 14, 2018: Development
Jennifer M SanMiguel, Lara K Abramowitz, Marisa S Bartolomei
Imprinted genes are expressed from one parental allele and regulated by differential DNA methylation at imprinting control regions (ICR). ICRs are reprogrammed in the germline through erasure and reestablishment of DNA methylation. Although much is known about DNA methylation establishment, DNA demethylation is less well understood. Recently, the Ten-Eleven Translocation proteins (TET1-3) have been shown to initiate DNA demethylation, with Tet1 -/- mice exhibiting aberrant levels of imprinted gene expression and ICR methylation...
March 12, 2018: Development
Hao Ge, Pingping Wu, Hong Qian, Sunney Xiaoliang Xie
Within an isogenic population, even in the same extracellular environment, individual cells can exhibit various phenotypic states. The exact role of stochastic gene-state switching regulating the transition among these phenotypic states in a single cell is not fully understood, especially in the presence of positive feedback. Recent high-precision single-cell measurements showed that, at least in bacteria, switching in gene states is slow relative to the typical rates of active transcription and translation...
March 12, 2018: PLoS Computational Biology
Jeffrey N Carey, Erin L Mettert, Manuela Roggiani, Kevin S Myers, Patricia J Kiley, Mark Goulian
Microbial populations can maximize fitness in dynamic environments through bet hedging, a process wherein a subpopulation assumes a phenotype not optimally adapted to the present environment but well adapted to an environment likely to be encountered. Here, we show that oxygen induces fluctuating expression of the trimethylamine oxide (TMAO) respiratory system of Escherichia coli, diversifying the cell population and enabling a bet-hedging strategy that permits growth following oxygen loss. This regulation by oxygen affects the variance in gene expression but leaves the mean unchanged...
February 26, 2018: Cell
Chandrani Das, Chaitanya Mokashi, Sharmila S Mande, Supreet Saini
The food-borne pathogen Salmonella typhimurium is a common cause of infections and diseases in a wide range of hosts. One of the major virulence factors associated to the infection process is flagella, which helps the bacterium swim to its preferred site of infection inside the host, the M-cells (Microfold cells) lining the lumen of the small intestine. The expression of flagellar genes is controlled by an intricate regulatory network. In this work, we investigate two aspects of flagella regulation and assembly: (a) distribution of the number of flagella in an isogenic population of bacteria and (b) dynamics of gene expression post cell division...
2018: Frontiers in Cellular and Infection Microbiology
Yen Ting Lin, Peter G Hufton, Esther J Lee, Davit A Potoyan
Pluripotent embryonic stem cells are of paramount importance for biomedical sciences because of their innate ability for self-renewal and differentiation into all major cell lines. The fateful decision to exit or remain in the pluripotent state is regulated by complex genetic regulatory networks. The rapid growth of single-cell sequencing data has greatly stimulated applications of statistical and machine learning methods for inferring topologies of pluripotency regulating genetic networks. The inferred network topologies, however, often only encode Boolean information while remaining silent about the roles of dynamics and molecular stochasticity inherent in gene expression...
February 16, 2018: PLoS Computational Biology
Pedro G Ferreira, Manuel Muñoz-Aguirre, Ferran Reverter, Caio P Sá Godinho, Abel Sousa, Alicia Amadoz, Reza Sodaei, Marta R Hidalgo, Dmitri Pervouchine, Jose Carbonell-Caballero, Ramil Nurtdinov, Alessandra Breschi, Raziel Amador, Patrícia Oliveira, Cankut Çubuk, João Curado, François Aguet, Carla Oliveira, Joaquin Dopazo, Michael Sammeth, Kristin G Ardlie, Roderic Guigó
Post-mortem tissues samples are a key resource for investigating patterns of gene expression. However, the processes triggered by death and the post-mortem interval (PMI) can significantly alter physiologically normal RNA levels. We investigate the impact of PMI on gene expression using data from multiple tissues of post-mortem donors obtained from the GTEx project. We find that many genes change expression over relatively short PMIs in a tissue-specific manner, but this potentially confounding effect in a biological analysis can be minimized by taking into account appropriate covariates...
February 13, 2018: Nature Communications
Wenbing Xie, Ioannis Kagiampakis, Lixia Pan, Yang W Zhang, Lauren Murphy, Yong Tao, Xiangqian Kong, Byunghak Kang, Limin Xia, Filipe L F Carvalho, Subhojit Sen, Ray-Whay Chiu Yen, Cynthia A Zahnow, Nita Ahuja, Stephen B Baylin, Hariharan Easwaran
Overall shared DNA methylation patterns between senescence (Sen) and cancers have led to the model that tumor-promoting epigenetic patterns arise through senescence. We show that transformation-associated methylation changes arise stochastically and independently of programmatic changes during senescence. Promoter hypermethylation events in transformation involve primarily pro-survival and developmental genes, similarly modified in primary tumors. Senescence-associated hypermethylation mainly involves metabolic regulators and appears early in proliferating "near-senescent" cells, which can be immortalized but are refractory to transformation...
February 12, 2018: Cancer Cell
Luiz Carlos Caires-Júnior, Ernesto Goulart, Uirá Souto Melo, Bruno Silva Henrique Araujo, Lucas Alvizi, Alessandra Soares-Schanoski, Danyllo Felipe de Oliveira, Gerson Shigeru Kobayashi, Karina Griesi-Oliveira, Camila Manso Musso, Murilo Sena Amaral, Lucas Ferreira daSilva, Renato Mancini Astray, Sandra Fernanda Suárez-Patiño, Daniella Cristina Ventini, Sérgio Gomes da Silva, Guilherme Lopes Yamamoto, Suzana Ezquina, Michel Satya Naslavsky, Kayque Alves Telles-Silva, Karina Weinmann, Vanessa van der Linden, Helio van der Linden, João Mendes Ricardo de Oliveira, Nivia Rodrigues Maria Arrais, Adriana Melo, Thalita Figueiredo, Silvana Santos, Joanna Castro Goes Meira, Saulo Duarte Passos, Roque Pacheco de Almeida, Ana Jovina Barreto Bispo, Esper Abrão Cavalheiro, Jorge Kalil, Edécio Cunha-Neto, Helder Nakaya, Robert Andreata-Santos, Luis Carlos de Souza Ferreira, Sergio Verjovski-Almeida, Paulo Lee Ho, Maria Rita Passos-Bueno, Mayana Zatz
Congenital Zika syndrome (CZS) causes early brain development impairment by affecting neural progenitor cells (NPCs). Here, we analyze NPCs from three pairs of dizygotic twins discordant for CZS. We compare by RNA-Seq the NPCs derived from CZS-affected and CZS-unaffected twins. Prior to Zika virus (ZIKV) infection the NPCs from CZS babies show a significantly different gene expression signature of mTOR and Wnt pathway regulators, key to a neurodevelopmental program. Following ZIKV in vitro infection, cells from affected individuals have significantly higher ZIKV replication and reduced cell growth...
February 2, 2018: Nature Communications
Hui Wang, Xiujun Cheng, Jinqiao Duan, Jürgen Kurths, Xiaofan Li
This work is devoted to investigating the evolution of concentration in a genetic regulation system, when the synthesis reaction rate is under additive and multiplicative asymmetric stable Lévy fluctuations. By focusing on the impact of skewness (i.e., non-symmetry) in the probability distributions of noise, we find that via examining the mean first exit time (MFET) and the first escape probability (FEP), the asymmetric fluctuations, interacting with nonlinearity in the system, lead to peculiar likelihood for transcription...
January 2018: Chaos
Yen Ting Lin, Nicolas E Buchler
Single-cell experiments show that gene expression is stochastic and bursty, a feature that can emerge from slow switching between promoter states with different activities. In addition to slow chromatin and/or DNA looping dynamics, one source of long-lived promoter states is the slow binding and unbinding kinetics of transcription factors to promoters, i.e. the non-adiabatic binding regime. Here, we introduce a simple analytical framework, known as a piecewise deterministic Markov process (PDMP), that accurately describes the stochastic dynamics of gene expression in the non-adiabatic regime...
January 2018: Journal of the Royal Society, Interface
Kevin D Mlynek, William E Sause, Derek E Moormeier, Marat R Sadykov, Kurt R Hill, Victor J Torres, Kenneth W Bayles, Shaun R Brinsmade
Staphylococcus aureus subverts innate defenses during infection in part by killing host immune cells to exacerbate disease. This human pathogen intercepts host cues and activates a transcriptional response via the S. aureus exoprotein expression (SaeR/S) two-component system to secrete virulence factors critical for pathogenesis. We recently showed that the transcriptional repressor CodY adjusts nuclease (nuc) gene expression via SaeR/S but the mechanism remained unknown. Herein, we identified two CodY binding motifs upstream of the sae P1 promoter, which suggested direct regulation by this global regulator...
January 29, 2018: Journal of Bacteriology
Dominique Chu
It is now widely accepted that biochemical reaction networks can perform computations. Examples are kinetic proof reading, gene regulation, or signalling networks. For many of these systems it was found that their computational performance is limited by a trade-off between the metabolic cost, the speed and the accuracy of the computation. In order to gain insight into the origins of these trade-offs, we consider entropy-driven computers as a model of biochemical computation. Using tools from stochastic thermodynamics, we show that entropy-driven computation is subject to a trade-off between accuracy and metabolic cost, but does not involve time-trade-offs...
April 14, 2018: Journal of Theoretical Biology
Davit A Potoyan, Peter G Wolynes
The complex genetic programs of eukaryotic cells are often regulated by key transcription factors occupying or clearing out of a large number of genomic locations. Orchestrating the residence times of these factors is therefore important for the well organized functioning of a large network. The classic models of genetic switches sidestep this timing issue by assuming the binding of transcription factors to be governed entirely by thermodynamic protein-DNA affinities. Here we show that relying on passive thermodynamics and random release times can lead to a "time-scale crisis" for master genes that broadcast their signals to a large number of binding sites...
November 2017: Physical Review. E
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