scholarly journals Limits of noise for autoregulated gene expression

2017 ◽  
Author(s):  
Peter Czuppon ◽  
Peter Pfaffelhuber
Keyword(s):  
Gene Expression ◽  
Negative Feedback ◽  
Positive Feedback ◽  
Fano Factor ◽  
Intrinsic Noise ◽  
Stochastic Averaging ◽  
Jump Processes ◽  
Markov Jump ◽  
Extrinsic Noise ◽  
Cellular Processes

AbstractGene 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. The technique we use is an extension of the Langevin approximation and is an application of a central limit theorem under stochastic averaging for Markov jump processes (Kang, Kurtz and Popovic, 2014). We find that (under our scaling and in equilibrium), negative feedback leads to a reduction in the Fano factor of at most 2, while the noise under positive feedback is potentially unbounded. The fit with simulations is very good and improves on known approximations.

scholarly journals Buffering gene expression noise by microRNA based feedforward regulation

2018 ◽  
Author(s):  
Pavol Bokes ◽  
Michal Hojcka ◽  
Abhyudai Singh
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Optimal Parameter ◽  
Kinetic Monte Carlo ◽  
Reaction Network ◽  
Fano Factor ◽  
Intrinsic Noise ◽  
Limit Function ◽  
Gene Expression Noise ◽  
Expression Noise

AbstractCells use various regulatory motifs, including feedforward loops, to control the intrinsic noise that arises in gene expression at low copy numbers. Here we study one such system, which is broadly inspired by the interaction between an mRNA molecule and an antagonistic microRNA molecule encoded by the same gene. The two reaction species are synchronously produced, individually degraded, and the second species (microRNA) exerts an antagonistic pressure on the first species (mRNA). Using linear-noise approximation, we show that the noise in the first species, which we quantify by the Fano factor, is sub-Poissonian, and exhibits a nonmonotonic response both to the species lifetime ratio and to the strength of the antagonistic interaction. Additionally, we use the Chemical Reaction Network Theory to prove that the first species distribution is Poissonian if the first species is much more stable than the second. Finally, we identify a special parametric regime, supporting a broad range of behaviour, in which the distribution can be analytically described in terms of the confluent hypergeometric limit function. We verify our analysis against large-scale kinetic Monte Carlo simulations. Our results indicate that, subject to specific physiological constraints, optimal parameter values can be found within the mRNA-microRNA motif that can benefit the cell by lowering the gene-expression noise.

scholarly journals Pathway dynamics can delineate the sources of transcriptional noise in gene expression

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Lucy Ham ◽  
Marcel Jackson ◽  
Michael Stumpf
Keyword(s):  
Intrinsic Noise ◽  
Stochastic Simulations ◽  
Transcriptional Noise ◽  
Extrinsic Noise ◽  
Cellular Processes ◽  
Dual Reporter ◽  
Extensive Cell ◽  
Noise In Gene Expression ◽  
Cell Expression ◽  
Cell To Cell Variability

Single-cell expression profiling opens up new vistas on cellular processes. Extensive cell-to-cell variability at the transcriptomic and proteomic level has been one of the stand-out observations. Because most experimental analyses are destructive we only have access to snapshot data of cellular states. This loss of temporal information presents significant challenges for inferring dynamics, as well as causes of cell-to-cell variability. In particular, we typically cannot separate dynamic variability from within cells ('intrinsic noise') from variability across the population ('extrinsic noise'). Here we make this non-identifiability mathematically precise, allowing us to identify new experimental set-ups that can assist in resolving this non-identifiability. We show that multiple generic reporters from the same biochemical pathways (e.g. mRNA and protein) can infer magnitudes of intrinsic and extrinsic transcriptional noise, identifying sources of heterogeneity. Stochastic simulations support our theory, and demonstrate that 'pathway-reporters' compare favourably to the well-known, but often difficult to implement, dual-reporter method.

scholarly journals Allele-specific single-cell RNA sequencing reveals different architectures of intrinsic and extrinsic gene expression noises

2019 ◽  
Author(s):  
Mengyi Sun ◽  
Jianzhi Zhang
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Intrinsic Noise ◽  
Mouse Fibroblast ◽  
Extrinsic Noise ◽  
Gene Expression Noise ◽  
Cell State ◽  
Single Cell Rna Sequencing ◽  
Allele Specific

ABSTRACTGene expression noise refers to the variation of the expression level of a gene among isogenic cells in the same environment, and has two sources: extrinsic noise arising from the disparity of the cell state and intrinsic noise arising from the stochastic process of gene expression in the same cell state. Due to the low throughput of the existing method for measuring the two noise components, the architectures of intrinsic and extrinsic expression noises remain elusive. Using allele-specific single-cell RNA sequencing, we here estimate the two noise components of 3975 genes in mouse fibroblast cells. Our analyses verify predicted influences of several factors such as the TATA-box and microRNA targeting on intrinsic and extrinsic noises and reveal gene function-associated noise trends implicating the action of natural selection. These findings unravel differential regulations, optimizations, and biological consequences of intrinsic and extrinsic noises and can aid the construction of desired synthetic circuits.

scholarly journals Inferring intrinsic and extrinsic noise from a dual fluorescent reporter

2016 ◽  
Author(s):  
Erik van Nimwegen
Keyword(s):  
Gene Expression ◽  
Bayesian Analysis ◽  
Ad Hoc ◽  
Intrinsic Noise ◽  
Extrinsic Noise ◽  
Fluorescent Reporter ◽  
Gene Expression Noise ◽  
Total Gene Expression ◽  
Using Data ◽  
Intrinsic And Extrinsic Noise

AbstractDual fluorescent reporter constructs, which measure gene expression from two identical promoters within the same cell, allow total gene expression noise to be decomposed into an extrinsic component, roughly associated with cell-to-cell fluctuations in cellular component concentrations, and intrinsic noise, roughly associated with inherent stochasticity of the biochemical reactions involved in gene expression [1]. A recent paper by Fu and Pachter presented frequentist statistical estimators for intrinsic and extrinsic noise using data from dual reporters [2]. For comparison, I here present results of a Bayesian analysis of this problem. I show that the orthodox estimators suffer from pathologies such as predicting negative values for a manifestly non-negative quantity, i.e. variance, and show that the Bayesian estimators do not suffer from such pathologies. In addition, I show that the Bayesian analysis automatically identifies that optimal estimates of intrinsic and extrinsic noise depend on a subtle combination of two statistics of the data, allowing for accuracies that are up to twice the accuracy of the orthodox estimators in some parameter regimes.I hope up this little worked out example contrasting orthodox statistical analysis based on ad hoc estimators with estimators resulting from a Bayesian analysis, will be educational for others in the field. I distribute a Mathematica Notebook with this paper that allows users to easily reproduce all results and figures of the paper.

scholarly journals Population growth affects intrinsic and extrinsic noise in gene expression

2018 ◽  
Author(s):  
Philipp Thomas
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Intrinsic Noise ◽  
Integrated Approach ◽  
Time Lapse ◽  
Biochemical Networks ◽  
Intrinsic Variability ◽  
Extrinsic Noise ◽  
Growing Population ◽  
Intrinsic And Extrinsic Noise

Clonal cells of exponentially growing populations vary substantially from cell to cell. The main drivers of this heterogeneity are the population dynamics and stochasticity in the intracellular reactions, which are commonly studied separately. Here we develop an agent-based framework that allows tracking of the biochemical dynamics in every single cell of a growing population that accounts for both of these factors. Apart from the common intrinsic variability of the biochemical reactions, the framework also predicts extrinsic noise arising from fluctuations in the histories of cells without the need to introduce fluctuating rate constants. Instead, these extrinsic fluctuations are explained by cell cycle fluctuations and differences in cell age, which are ubiquitously observed in growing populations. We give explicit formulas to quantify mean molecule numbers, intrinsic and extrinsic noise statistics as measured in two-colour experiments. We find that these statistics may differ significantly depending on the experimental setup used to observe the cells. We illustrate this fact using (i) averages over an isolated cell lineage tracked over many generations as observed in the mother machine, (ii) snapshots of a growing population with known cell ages as recorded in time-lapse microscopy, and (iii) snapshots of unknown cell ages as measured from static images. Our integrated approach applies to arbitrary biochemical networks and generation time distributions. By employing models of stochastic gene expression and feedback regulation, we elucidate that isolated lineages, as compared to snapshot data, can significantly overestimate the mean number of molecules, overestimate extrinsic noise but underestimate intrinsic noise and have qualitatively different sensitivities to cell cycle fluctuations.

scholarly journals Coupled Positive and Negative Feedbacks Produce Diverse Gene Expression Patterns in Colonies

mBio ◽  
2015 ◽  
Vol 6 (2) ◽  
Author(s):  
Namiko Mitarai ◽  
Mogens Høgh Jensen ◽  
Szabolcs Semsey
Keyword(s):  
Gene Expression ◽  
Microbial Communities ◽  
Protein Content ◽  
Computer Simulations ◽  
Negative Feedback ◽  
Positive Feedback ◽  
Feedback Loop ◽  
Expression Patterns ◽  
Molecular Networks ◽  
Gene Expression Patterns

ABSTRACTFormation of patterns is a common feature in the development of multicellular organism as well as of microbial communities. To investigate the formation of gene expression patterns in colonies, we build a mathematical model of two-dimensional colony growth, where cells carry a coupled positive-and-negative-feedback circuit. We demonstrate that the model can produce sectored, target (concentric), uniform, and scattered expression patterns of regulators, depending on gene expression dynamics and nutrient diffusion. We reconstructed the same regulatory structure inEscherichia colicells and found gene expression patterns on the surface of colonies similar to the ones produced by the computer simulations. By comparing computer simulations and experimental results, we observed that very simple rules of gene expression can yield a spectrum of well-defined patterns in a growing colony. Our results suggest that variations of the protein content among cells lead to a high level of heterogeneity in colonies.IMPORTANCEFormation of patterns is a common feature in the development of microbial communities. In this work, we show that a simple genetic circuit composed of a positive-feedback loop and a negative-feedback loop can produce diverse expression patterns in colonies. We obtained similar sets of gene expression patterns in the simulations and in the experiments. Because the combination of positive feedback and negative feedback is common in intracellular molecular networks, our results suggest that the protein content of cells is highly diversified in colonies.

scholarly journals Allele-specific single-cell RNA sequencing reveals different architectures of intrinsic and extrinsic gene expression noises

2019 ◽  
Vol 48 (2) ◽  
pp. 533-547 ◽  
Author(s):  
Mengyi Sun ◽  
Jianzhi Zhang
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Intrinsic Noise ◽  
Mouse Fibroblast ◽  
Extrinsic Noise ◽  
Gene Expression Noise ◽  
Cell State ◽  
Single Cell Rna Sequencing ◽  
Allele Specific

Abstract Gene expression noise refers to the variation of the expression level of a gene among isogenic cells in the same environment, and has two sources: extrinsic noise arising from the disparity of the cell state and intrinsic noise arising from the stochastic process of gene expression in the same cell state. Due to the low throughput of the existing method for measuring the two noise components, the architectures of intrinsic and extrinsic expression noises remain elusive. Using allele-specific single-cell RNA sequencing, we here estimate the two noise components of 3975 genes in mouse fibroblast cells. Our analyses verify predicted influences of several factors such as the TATA-box and microRNA targeting on intrinsic or extrinsic noises and reveal gene function-associated noise trends implicating the action of natural selection. These findings unravel differential regulations, optimizations, and biological consequences of intrinsic and extrinsic noises and can aid the construction of desired synthetic circuits.

Asymptotic normality for discretely observed Markov jump processes with an absorbing state

2014 ◽  
Vol 90 ◽  
pp. 136-139 ◽  
Author(s):  
Alexander Kremer ◽  
Rafael Weißbach
Keyword(s):  
Asymptotic Normality ◽  
Jump Processes ◽  
Markov Jump ◽  
Markov Jump Processes ◽  
Absorbing State

scholarly journals Mitochondrial Glucocorticoid Receptors and Their Actions

2021 ◽  
Vol 22 (11) ◽  
pp. 6054
Author(s):  
Ioanna Kokkinopoulou ◽  
Paraskevi Moutsatsou
Keyword(s):  
Gene Expression ◽  
Glucocorticoid Receptors ◽  
Mitochondrial Gene ◽  
Cell Types ◽  
Ros Generation ◽  
Mitochondrial Gene Expression ◽  
Mitochondrial Energy Metabolism ◽  
Bcl2 Family ◽  
Cellular Processes ◽  
Almost All

Mitochondria are membrane organelles present in almost all eukaryotic cells. In addition to their well-known role in energy production, mitochondria regulate central cellular processes, including calcium homeostasis, Reactive Oxygen Species (ROS) generation, cell death, thermogenesis, and biosynthesis of lipids, nucleic acids, and steroid hormones. Glucocorticoids (GCs) regulate the mitochondrially encoded oxidative phosphorylation gene expression and mitochondrial energy metabolism. The identification of Glucocorticoid Response Elements (GREs) in mitochondrial sequences and the detection of Glucocorticoid Receptor (GR) in mitochondria of different cell types gave support to hypothesis that mitochondrial GR directly regulates mitochondrial gene expression. Numerous studies have revealed changes in mitochondrial gene expression alongside with GR import/export in mitochondria, confirming the direct effects of GCs on mitochondrial genome. Further evidence has made clear that mitochondrial GR is involved in mitochondrial function and apoptosis-mediated processes, through interacting or altering the distribution of Bcl2 family members. Even though its exact translocation mechanisms remain unknown, data have shown that GR chaperones (Hsp70/90, Bag-1, FKBP51), the anti-apoptotic protein Bcl-2, the HDAC6- mediated deacetylation and the outer mitochondrial translocation complexes (Tom complexes) co-ordinate GR mitochondrial trafficking. A role of mitochondrial GR in stress and depression as well as in lung and hepatic inflammation has also been demonstrated.

scholarly journals Exact statistical solution for the hopping transport of trapped charge via finite Markov jump processes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Andrey A. Pil’nik ◽  
Andrey A. Chernov ◽  
Damir R. Islamov
Keyword(s):  
Charge Transport ◽  
Thin Layers ◽  
Jump Processes ◽  
Dielectric Films ◽  
Algebraic Equations ◽  
Markov Jump ◽  
Statistical Solution ◽  
Linear Algebraic Equations ◽  
Special Cases ◽  
Thin Dielectric Films

AbstractIn this study, we developed a discrete theory of the charge transport in thin dielectric films by trapped electrons or holes, that is applicable both for the case of countable and a large number of traps. It was shown that Shockley–Read–Hall-like transport equations, which describe the 1D transport through dielectric layers, might incorrectly describe the charge flow through ultra-thin layers with a countable number of traps, taking into account the injection from and extraction to electrodes (contacts). A comparison with other theoretical models shows a good agreement. The developed model can be applied to one-, two- and three-dimensional systems. The model, formulated in a system of linear algebraic equations, can be implemented in the computational code using different optimized libraries. We demonstrated that analytical solutions can be found for stationary cases for any trap distribution and for the dynamics of system evolution for special cases. These solutions can be used to test the code and for studying the charge transport properties of thin dielectric films.

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