scholarly journals Independent control of mean and noise by convolution of gene expression distributions

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Karl P. Gerhardt ◽  
Satyajit D. Rao ◽  
Evan J. Olson ◽  
Oleg A. Igoshin ◽  
Jeffrey J. Tabor
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Probability Theory ◽  
Biological Pathways ◽  
Cellular Heterogeneity ◽  
High Noise ◽  
Gene Expression Noise ◽  
Inducible Promoters ◽  
Expression Noise ◽  
Scaling Relationship

AbstractGene expression noise can reduce cellular fitness or facilitate processes such as alternative metabolism, antibiotic resistance, and differentiation. Unfortunately, efforts to study the impacts of noise have been hampered by a scaling relationship between noise and expression level from individual promoters. Here, we use theory to demonstrate that mean and noise can be controlled independently by expressing two copies of a gene from separate inducible promoters in the same cell. We engineer low and high noise inducible promoters to validate this result in Escherichia coli, and develop a model that predicts the experimental distributions. Finally, we use our method to reveal that the response of a promoter to a repressor is less sensitive with higher repressor noise and explain this result using a law from probability theory. Our approach can be applied to investigate the effects of noise on diverse biological pathways or program cellular heterogeneity for synthetic biology applications.

scholarly journals Independent control of mean and noise by convolution of gene expression distributions

2021 ◽  
Author(s):  
Karl P. Gerhardt ◽  
Satyajit D. Rao ◽  
Evan J. Olson ◽  
Oleg A. Igoshin ◽  
Jeffrey J. Tabor
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Low Noise ◽  
Biological Pathways ◽  
Cellular Heterogeneity ◽  
Gene Expression Noise ◽  
Inducible Promoters ◽  
Expression Noise ◽  
Scaling Relationship ◽  
Single Promoter

AbstractGene expression noise can reduce cellular fitness or facilitate processes such as alternative metabolism, antibiotic resistance, and differentiation. Unfortunately, efforts to study the impacts of noise have been hampered by a scaling relationship between noise and expression level from a single promoter. Here, we use theory to demonstrate that mean and noise can be controlled independently by expressing two copies of a gene from separate inducible promoters in the same cell. We engineer high- and low-noise inducible promoters to validate this result in Escherichia coli, and develop a model that predicts the experimental distributions. Finally, we use our method to reveal that the response of a promoter to a repressor is less sensitive with higher repressor noise, and explain this result using a law from probability theory. Our approach can be applied to investigate the effects of noise on diverse biological pathways or program cellular heterogeneity for synthetic biology applications.

scholarly journals Flagellar dynamics reveal large fluctuations and kinetic limit in the Escherichia coli chemotaxis network

2020 ◽  
Author(s):  
Roshni Bano ◽  
Patrick Mears ◽  
Ido Golding ◽  
Yann R. Chemla
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Steady State ◽  
Network Activity ◽  
Signaling Networks ◽  
Changing Environment ◽  
Gene Expression Noise ◽  
Expression Noise ◽  
Flagellar Motors ◽  
Large Fluctuations

AbstractBiochemical signaling networks allow living cells to adapt to a changing environment, but these networks must cope with unavoidable number fluctuations (“noise”) in their molecular constituents. Escherichia coli chemotaxis, by which bacteria modulate their random run/tumble swimming pattern to navigate their environment, is a paradigm for the role of noise in cell signaling. The key signaling protein, CheY, when activated by (reversible) phosphorylation, causes a switch in the rotational direction of the flagellar motors propelling the cell, leading to tumbling. CheY-P concentration, [CheY-P], is thus a measure of the chemotaxis network’s output, and temporal fluctuations in [CheY-P] provide a proxy for network noise. However, measuring these fluctuations in the single cell, at the relevant timescale of individual run and tumble events, remains a challenge. Here we quantify the short-timescale (0.5-5 s) fluctuations in [CheY-P] from the switching dynamics of individual flagella, observed using time-resolved fluorescence microscopy of optically trapped E. coli cells. This approach reveals large [CheY-P] fluctuations at steady state, which may play a critical role in driving flagellar switching and cell tumbling. A stochastic theoretical model, inspired by work on gene expression noise, points to CheY activation occurring in bursts, driving the large [CheY-P] fluctuations. When the network is stimulated chemically to higher activity, we observe a dramatic decrease in [CheY-P] fluctuations. Our stochastic model shows that an intrinsic kinetic ceiling on network activity places an upper limit on [CheY-P], which when encountered suppresses its fluctuations. This limit may also prevent cells from tumbling unproductively in steep gradients.Significance StatementBacteria use intracellular signaling networks to navigate and adapt to their changing environment. These networks must cope with fluctuations in their molecular constituents, but the role this noise plays in cell behavior is not well understood. Here, we present a novel approach to quantify network noise in individual Escherichia coli cells. Our measurements show that the network exhibits larger-than-expected fluctuations when operating at a steady state; these fluctuations decrease dramatically when the network is activated by a chemical stimulus. A model inspired by gene expression noise studies recapitulates our findings and suggests that large fluctuations are driven by ‘bursts’ in signaling, drawing a parallel between the operating principles of gene regulatory and protein signaling networks.

scholarly journals A plasmid-basedEscherichia coligene expression system with cell-to-cell variation below the extrinsic noise limit

2017 ◽  
Author(s):  
Zach Hensel
Keyword(s):  
Gene Expression ◽  
Protein Expression ◽  
Dynamic Range ◽  
Expression System ◽  
Expression Systems ◽  
High Noise ◽  
Gene Expression Noise ◽  
Expression Levels ◽  
Expression Noise ◽  
Negative Autoregulation

AbstractExperiments in synthetic biology and microbiology can benefit from protein expression systems with low cell-to-cell variability (noise) and expression levels precisely tunable across a useful dynamic range. Despite advances in understanding the molecular biology of microbial gene regulation, many experiments employ protein-expression systems exhibiting high noise and nearly all-or-none responses to induction. I present an expression system that incorporates elements known to reduce gene expression noise: negative autoregulation and bicistronic transcription. I show by stochastic simulation that while negative autoregulation can produce a more gradual response to induction, bicistronic expression of a repressor and gene of interest can be necessary to reduce noise below the extrinsic limit. I synthesized a plasmid-based system incorporating these principles and studied its properties inEscherichia colicells, using flow cytometry and fluorescence microscopy to characterize induction dose-response, induction/repression kinetics and gene expression noise. By varying ribosome binding site strengths, expression levels from 55— 10,740 molecules/cell were achieved with noise below the extrinsic limit. Individual strains are inducible across a dynamic range greater than 20-fold. Experimental comparison of different regulatory networks confirmed that bicistronic autoregulation reduces noise, and revealed unexpectedly high noise for a conventional expression system with a constitutively expressed transcriptional repressor. I suggest a hybrid, low-noise expression system to increase the dynamic range.

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 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.

scholarly journals SIR2 Expression Noise Can Generate Heterogeneity in Viability but Does Not Affect Cell-to-Cell Epigenetic Silencing of Subtelomeric URA3 in Yeast

2020 ◽  
Vol 10 (9) ◽  
pp. 3435-3443
Author(s):  
Jian Liu ◽  
Laureline Mosser ◽  
Catherine Botanch ◽  
Jean-Marie François ◽  
Jean-Pascal Capp
Keyword(s):  
Gene Expression ◽  
Saccharomyces Cerevisiae ◽  
Epigenetic Modification ◽  
Epigenetic Silencing ◽  
Cell Heterogeneity ◽  
Gene Expression Noise ◽  
Expression Noise ◽  
Cell Expression ◽  
Cell To Cell Variability ◽  
Epigenetic Processes

Abstract Chromatin structure clearly modulates gene expression noise, but the reverse influence has never been investigated, namely how the cell-to-cell expression heterogeneity of chromatin modifiers may generate variable rates of epigenetic modification. Sir2 is a well-characterized histone deacetylase of the Sirtuin family. It strongly influences chromatin silencing, especially at telomeres, subtelomeres and rDNA. This ability to influence epigenetic landscapes makes it a good model to study the largely unexplored interplay between gene expression noise and other epigenetic processes leading to phenotypic diversification. Here, we addressed this question by investigating whether noise in the expression of SIR2 was associated with cell-to-cell heterogeneity in the frequency of epigenetic silencing at subtelomeres in Saccharomyces cerevisiae. Using cell sorting to isolate subpopulations with various expression levels, we found that heterogeneity in the cellular concentration of Sir2 does not lead to heterogeneity in the epigenetic silencing of subtelomeric URA3 between these subpopulations. We also noticed that SIR2 expression noise can generate cell-to-cell variability in viability, with lower levels being associated with better viability. This work shows that SIR2 expression fluctuations are not sufficient to generate cell-to-cell heterogeneity in the epigenetic silencing of URA3 at subtelomeres in Saccharomyces cerevisiae but can strongly affect cellular viability.

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