scholarly journals Promoter and transcription factor dynamics tune protein mean and noise strength in a quorum sensing-based feedback synthetic circuit

2017 ◽  
Author(s):  
Yadira Boada ◽  
Alejandro Vignoni ◽  
Jesús Picó
Keyword(s):  
Gene Expression ◽  
Quorum Sensing ◽  
Negative Feedback ◽  
In Silico ◽  
Stochastic Simulations ◽  
Expression Level ◽  
Gene Expression Noise ◽  
Expression Noise ◽  
Synthetic Circuit ◽  
The Mean

AbstractGene expression is a fundamental cellular process. Its stochastic fluctuations due to intrinsic and extrinsic sources, known generically as ‘gene expression noise’, trigger both beneficial and harmful consequences for the cell behavior.Controlling gene expression noise is of interest in many applications in biotechnology, biomedicine and others. Yet, control of the mean expression level is an equally desirable goal. Here, we analyze a gene synthetic network designed to reduce gene expression noise while achieving a desired mean expression level. The circuit combines a negative feedback loop over the gene of interest, and a cell-to-cell communication mechanism based on quorum sensing. We analyze the ability of the circuit to reduce noise as a function of parameters that can be tuned in the wet-lab, and the role quorum sensing plays. Intrinsic noise is generated by the inherent stochasticity of biochemical reactions. On the other hand, extrinsic noise is due to variability in the cell environment and the amounts of cellular components that affect gene expression. We develop a realistic model of the gene synthetic circuit over the population of cells using mass action kinetics and the stochastic Chemical Langevin Equation to include intrinsic noise, with parameters drawn from a distribution to account for extrinsic noise. Stochastic simulations allow us to quantify the mean expression level and noise strength of all species under different scenarios, showing good agreement with system-wide available experimental data of protein abundance and noise inE. coli. Ourin silicoexperiments reveal significant noise attenuation in gene expression through the interplay between quorum sensing and the negative feedback, allowing control of the mean expression and variance of the protein of interest. Thesein silicoconclusions are validated by preliminary experimental results. This gene network could have important implications as a robust protein production system in industrial biotechnology.Author SummaryControlling gene expression level is of interest in many applications in biotechnology, biomedicine and others. Yet, the stochastic nature of biochemical reactions plays an important role in biological systems, and cannot be disregarded. Gene expression noise resulting from this stochasticity has been studied over the past years bothin vivo, andin silicousing mathematical models. Nowadays, synthetic biology approaches allow to design novel biological circuits, drawing on principles elucidated from biology and engineering, for the purpose of decoupled control of mean gene expression and its variance. We propose a gene synthetic circuit with these characteristics, using negative feedback and quorum sensing based cell-to-cell communication to induce population consensus. Ourin silicoanalysis using stochastic simulations with a realistic model reveal significant noise attenuation in gene expression through the interplay between quorum sensing and the negative feedback, allowing control of the mean expression and variance of the protein of interest. Preliminaryin vivoresults fully agree with the computational ones.

scholarly journals Fitness effects of altering gene expression noise in Saccharomyces cerevisiae

2018 ◽  
Author(s):  
Fabien Duveau ◽  
Andrea Hodgins-Davis ◽  
Brian P.H. Metzger ◽  
Bing Yang ◽  
Stephen Tryban ◽  
...  
Keyword(s):  
Gene Expression ◽  
Saccharomyces Cerevisiae ◽  
Expression Level ◽  
Gene Expression Noise ◽  
Expression Levels ◽  
Fitness Effects ◽  
Expression Noise ◽  
Average Expression Level ◽  
The Difference ◽  
The Impact

AbstractGene expression noise is an evolvable property of biological systems that describes differences in gene expression among genetically identical cells in the same environment. Prior work has shown that expression noise is heritable and can be shaped by natural selection, but the impact of variation in expression noise on organismal fitness has proven difficult to measure. Here, we quantify the fitness effects of altering expression noise for the TDH3 gene in Saccharomyces cerevisiae. We show that increases in expression noise can be deleterious or beneficial depending on the difference between the average expression level of a genotype and the expression level maximizing fitness. We also show that a simple model relating single-cell expression levels to population growth produces patterns that are consistent with our empirical data. We use this model to explore a broad range of average expression levels and expression noise, providing additional insight into the fitness effects of variation in expression noise.

Gene expression noise randomizes the adaptive response to DNA alkylation damage in E. coli

2019 ◽  
Author(s):  
Stephan Uphoff
Keyword(s):  
Gene Expression ◽  
Dna Damage ◽  
Adaptive Response ◽  
Direct Consequence ◽  
Quantitative Model ◽  
Stochastic Simulations ◽  
Gene Expression Noise ◽  
Expression Noise ◽  
Ada Protein ◽  
Random Fluctuations

DNA damage caused by alkylating chemicals induces an adaptive response in Escherichia coli cells that increases their tolerance to further damage. Signalling of the response occurs through methylation of the Ada protein which acts as a damage sensor and induces its own gene expression through a positive feedback loop. However, random fluctuations in the abundance of Ada jeopardize the reliability of the induction signal. I developed a quantitative model to test how gene expression noise and feedback amplification affect the fidelity of the adaptive response. A remarkably simple model accurately reproduced experimental observations from single-cell measurements of gene expression dynamics in a microfluidic device. Stochastic simulations showed that delays in the adaptive response are a direct consequence of the very low number of Ada molecules present to signal DNA damage. For cells that have zero copies of Ada, response activation becomes a memoryless process that is dictated by an exponential waiting time distribution between basal Ada expression events. Experiments also confirmed the model prediction that the strength of the adaptive response drops with increasing growth rate of cells.

scholarly journals Double-edged role of resource competition in gene expression noise and control

2021 ◽  
Author(s):  
Hanah Goetz ◽  
Austin Stone ◽  
Rong Zhang ◽  
Ying-Cheng Lai ◽  
Xiaojun Tian
Keyword(s):  
Gene Expression ◽  
Noise Reduction ◽  
Negative Feedback ◽  
Resource Competition ◽  
Control Strategies ◽  
Protein Biosynthesis ◽  
Resource Constraint ◽  
Gene Expression Noise ◽  
Expression Noise

Despite extensive investigation demonstrating that resource competition can significantly alter the circuits' deterministic behaviors, a fundamental issue is how resource competition contributes to the gene expression noise and how the noise can be controlled. Utilizing a two-gene circuit as a prototypical system, we uncover a surprising double-edged role of resource competition in gene expression noise: the competition decreases noise through a resource constraint but generates its own type of noise which we name as ''resource competitive noise.'' Utilization of orthogonal resources enables retaining the noise reduction conferred by resource constraint while removing the added resource competitive noise. The noise reduction effects are studied using three negative feedback controller types: negatively competitive regulation (NCR), local, and global controllers, each having four placement architectures in the protein biosynthesis pathway (mRNA or protein inhibition on transcription or translation). Our results show that both local and NCR controllers with mRNA-mediated inhibition are efficacious at reducing noise, with NCR controllers demonstrating a superior noise-reduction capability. We also find that combining negative feedback controllers with orthogonal resources can improve the local controllers. This work provides deep insights into the origin of stochasticity in gene circuits with resource competition and guidance for developing effective noise control strategies.

scholarly journals Fitness effects of altering gene expression noise in Saccharomyces cerevisiae

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Fabien Duveau ◽  
Andrea Hodgins-Davis ◽  
Brian PH Metzger ◽  
Bing Yang ◽  
Stephen Tryban ◽  
...  
Keyword(s):  
Gene Expression ◽  
Saccharomyces Cerevisiae ◽  
Expression Level ◽  
Gene Expression Noise ◽  
Expression Levels ◽  
Fitness Effects ◽  
Expression Noise ◽  
Average Expression Level ◽  
The Difference ◽  
The Impact

Gene expression noise is an evolvable property of biological systems that describes differences in expression among genetically identical cells in the same environment. Prior work has shown that expression noise is heritable and can be shaped by selection, but the impact of variation in expression noise on organismal fitness has proven difficult to measure. Here, we quantify the fitness effects of altering expression noise for the TDH3 gene in Saccharomyces cerevisiae. We show that increases in expression noise can be deleterious or beneficial depending on the difference between the average expression level of a genotype and the expression level maximizing fitness. We also show that a simple model relating single-cell expression levels to population growth produces patterns consistent with our empirical data. We use this model to explore a broad range of average expression levels and expression noise, providing additional insight into the fitness effects of variation in expression noise.

Reduction in gene expression noise by targeted increase in accessibility at gene loci

2021 ◽  
Vol 118 (42) ◽  
pp. e2018640118
Author(s):  
LaTasha C. R. Fraser ◽  
Ryan J. Dikdan ◽  
Supravat Dey ◽  
Abhyudai Singh ◽  
Sanjay Tyagi
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Single Molecule ◽  
Single Cells ◽  
Global Changes ◽  
Messenger Rnas ◽  
Histone Acetyl Transferase ◽  
Gene Expression Noise ◽  
Expression Noise ◽  
Eukaryotic Genes

Many eukaryotic genes are expressed in randomly initiated bursts that are punctuated by periods of quiescence. Here, we show that the intermittent access of the promoters to transcription factors through relatively impervious chromatin contributes to this “noisy” transcription. We tethered a nuclease-deficient Cas9 fused to a histone acetyl transferase at the promoters of two endogenous genes in HeLa cells. An assay for transposase-accessible chromatin using sequencing showed that the activity of the histone acetyl transferase altered the chromatin architecture locally without introducing global changes in the nucleus and rendered the targeted promoters constitutively accessible. We measured the gene expression variability from the gene loci by performing single-molecule fluorescence in situ hybridization against mature messenger RNAs (mRNAs) and by imaging nascent mRNA molecules present at active gene loci in single cells. Because of the increased accessibility of the promoter to transcription factors, the transcription from two genes became less noisy, even when the average levels of expression did not change. In addition to providing evidence for chromatin accessibility as a determinant of the noise in gene expression, our study offers a mechanism for controlling gene expression noise which is otherwise unavoidable.

scholarly journals CpG island composition differences are a source of gene expression noise indicative of promoter responsiveness

2018 ◽  
Vol 19 (1) ◽  
Author(s):  
Michael D. Morgan ◽  
John C. Marioni
Keyword(s):  
Gene Expression ◽  
Cpg Island ◽  
Gene Expression Noise ◽  
Expression Noise

scholarly journals Enhancement of gene expression noise due to nonspecific transcription factor binding

2019 ◽  
Author(s):  
Supravat Dey ◽  
Mohammad Soltani ◽  
Abhyudai Singh
Keyword(s):  
Gene Expression ◽  
Stochastic Dynamics ◽  
Gene Expression Noise ◽  
Downstream Target ◽  
High Affinity ◽  
Expression Noise ◽  
Degradation Rates ◽  
Poisson Limit ◽  
Random Fluctuations

ABSTRACTThe genome contains several high-affinity non-functional binding sites for transcription factors (TFs) creating a hidden and unexplored layer of gene regulation. We investigate the role of such “decoy sites” in controlling noise (random fluctuations) in the level of a TF that is synthesized in stochastic bursts. Prior studies have assumed that decoy-bound TFs are protected from degradation, and in this case decoys function to buffer noise. Relaxing this assumption to consider arbitrary degradation rates for both bound/unbound TF states, we find rich noise behaviors. For low-affinity decoys, noise in the level of unbound TF always monotonically decreases to the Poisson limit with increasing decoy numbers. In contrast, for high affinity decoys, noise levels first increase with increasing decoy numbers, before decreasing back to the Poisson limit. Interestingly, while protection of bound TFs from degradation slows the time-scale of fluctuations in the unbound TF levels, decay of bounds TFs leads to faster fluctuations and smaller noise propagation to downstream target proteins. In summary, our analysis reveals stochastic dynamics emerging from nonspecific binding of TFs, and highlight the dual role of decoys as attenuators or amplifiers of gene expression noise depending on their binding affinity and stability of the bound TF.

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