scholarly journals Noise propagation shapes condition-dependent gene expression noise in Escherichia coli

2019 ◽  
Author(s):  
Arantxa Urchueguía ◽  
Luca Galbusera ◽  
Gwendoline Bellement ◽  
Thomas Julou ◽  
Erik van Nimwegen
Keyword(s):  
Gene Expression ◽  
Growth Conditions ◽  
Transcriptional Noise ◽  
Noise Propagation ◽  
Gene Expression Noise ◽  
E Coli ◽  
Expression Noise ◽  
Rate Dependent ◽  
Genome Wide ◽  
Principal Axes

AbstractAlthough it is well appreciated that gene expression is inherently noisy and that transcriptional noise is encoded in a promoter’s sequence, little is known about the variation in transcriptional noise across growth conditions. Using flow cytometry we here quantify transcriptional noise in E. coli genome-wide across 8 growth conditions, and find that noise and gene regulation are intimately coupled. Apart from a growth-rate dependent lower bound on noise, we find that individual promoters show highly condition-dependent noise and that condition-dependent expression noise is shaped by noise propagation from regulators to their targets. A simple model of noise propagation identifies TFs that most contribute to both condition-specific and condition-independent noise propagation. The overall correlation structure of sequence and expression properties of E. coli genes uncovers that genes are organized along two principal axes, with the first axis sorting genes by their mean expression and evolutionary rate of their coding regions, and the second axis sorting genes by their expression noise, the number of regulatory inputs in their promoter, and their expression plasticity.

scholarly journals Genome-wide gene expression noise in Escherichia coli is condition-dependent and determined by propagation of noise through the regulatory network

PLoS Biology ◽  
2021 ◽  
Vol 19 (12) ◽  
pp. e3001491
Author(s):  
Arantxa Urchueguía ◽  
Luca Galbusera ◽  
Dany Chauvin ◽  
Gwendoline Bellement ◽  
Thomas Julou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Growth Rate ◽  
Regulatory Network ◽  
Growth Conditions ◽  
Noise Levels ◽  
Transcriptional Noise ◽  
Expression Noise ◽  
Genome Wide ◽  
Absolute Expression

Although it is well appreciated that gene expression is inherently noisy and that transcriptional noise is encoded in a promoter’s sequence, little is known about the extent to which noise levels of individual promoters vary across growth conditions. Using flow cytometry, we here quantify transcriptional noise in Escherichia coli genome-wide across 8 growth conditions and find that noise levels systematically decrease with growth rate, with a condition-dependent lower bound on noise. Whereas constitutive promoters consistently exhibit low noise in all conditions, regulated promoters are both more noisy on average and more variable in noise across conditions. Moreover, individual promoters show highly distinct variation in noise across conditions. We show that a simple model of noise propagation from regulators to their targets can explain a significant fraction of the variation in relative noise levels and identifies TFs that most contribute to both condition-specific and condition-independent noise propagation. In addition, analysis of the genome-wide correlation structure of various gene properties shows that gene regulation, expression noise, and noise plasticity are all positively correlated genome-wide and vary independently of variations in absolute expression, codon bias, and evolutionary rate. Together, our results show that while absolute expression noise tends to decrease with growth rate, relative noise levels of genes are highly condition-dependent and determined by the propagation of noise through the gene regulatory network.

scholarly journals Plasmids for independently tunable, low-noise expression of two genes

2019 ◽  
Author(s):  
João P. N. Silva ◽  
Soraia Vidigal Lopes ◽  
Diogo J. Grilo ◽  
Zach Hensel
Keyword(s):  
Gene Expression ◽  
Single Molecule ◽  
Single Gene ◽  
Growth Conditions ◽  
Low Noise ◽  
Extrinsic Noise ◽  
Gene Expression Noise ◽  
Expression Noise ◽  
Compatible Plasmid ◽  
Noise Limit

AbstractSome microbiology experiments and biotechnology applications can be improved if it is possible to tune the expression of two different genes at the same time with cell-to-cell variation at or below the level of genes constitutively expressed from the chromosome (the “extrinsic noise limit”). This was recently achieved for a single gene by exploiting negative autoregulation by the tetracycline repressor (TetR) and bicistronic gene expression to reduce gene expression noise. We report new plasmids that use the same principles to achieve simultaneous, low-noise expression for two genes. The TetR system was moved to a compatible plasmid backbone, and a system based on the lac repressor (LacI) was found to also exhibit gene expression noise below the extrinsic noise limit. We characterize gene expression mean and noise across the range of induction levels for these plasmids, apply the LacI system to tune expression for single-molecule mRNA detection in two different growth conditions, and show that two plasmids can be co-transformed to independently tune expression of two different genes.

scholarly journals Subpopulations of sensorless bacteria drive fitness in fluctuating environments

2020 ◽  
Author(s):  
Thomas Julou ◽  
Ludovit Zweifel ◽  
Diana Blank ◽  
Athos Fiori ◽  
Erik van Nimwegen
Keyword(s):  
Gene Expression ◽  
Single Molecule ◽  
Population Level ◽  
General Mechanism ◽  
Gene Expression Noise ◽  
E Coli ◽  
Expression Noise ◽  
Basal Expression ◽  
Fluctuating Environments ◽  
Operon Expression

AbstractPopulations of bacteria often undergo a lag in growth when switching conditions. Because growth lags can be large compared to typical doubling times, variations in growth lag are an important but often overlooked component of bacterial fitness in fluctuating environments. We here explore how growth lag variation is determined for the archetypical switch from glucose to lactose as a carbon source in E. coli. First, we show that single-cell lags are bimodally distributed and controlled by a single-molecule trigger. That is, gene expression noise causes the population before the switch to divide cells with zero pre-existing into subpopulations with zero and nonzero lac operon expression. While ’sensorless’ lac expression at the switch have long lags because they are unable to sense the lactose signal, any nonzero lac operon expression suffices to ensure a short lag. Second, we show that the growth lag at the population level depends crucially on the fraction of sensorless cells, and that this fraction in turn depends sensitively on the growth condition before the switch. Consequently, even small changes in basal expression affecting the fraction of sensorless cells can significantly affect population lags and fitness under switching conditions, and may thus be subject to significant natural selection. Indeed, we show that condition-dependent population lags vary across wild E. coli isolates. Since many sensory genes are naturally low expressed in conditions where their inducer is not present, bimodal responses due to subpopulations of sensorless cells may be a general mechanism inducing phenotypic heterogeneity and controlling population lags in switching environments. This mechanism also illustrates how gene expression noise can turn even simple sensory gene circuits into a bet-hedging module, and underlines the profound role of gene expression noise in regulatory responses.

scholarly journals Controlling E. coli Gene Expression Noise

2015 ◽  
Vol 9 (4) ◽  
pp. 497-504 ◽  
Author(s):  
Kyung Hyuk Kim ◽  
Kiri Choi ◽  
Bryan Bartley ◽  
Herbert M. Sauro
Keyword(s):  
Gene Expression ◽  
Gene Expression Noise ◽  
E Coli ◽  
Expression Noise

scholarly journals Cis-Regulatory Logic Produces Gene-Expression Noise Describing Phenotypic Heterogeneity in Bacteria

2021 ◽  
Vol 12 ◽  
Author(s):  
Debajyoti Chowdhury ◽  
Chao Wang ◽  
Aiping Lu ◽  
Hailong Zhu
Keyword(s):  
Gene Expression ◽  
Phenotypic Variability ◽  
Regulatory Elements ◽  
Phenotypic Heterogeneity ◽  
Animal Cells ◽  
Gene Expression Noise ◽  
Expression Noise ◽  
Promoter Architecture ◽  
Genome Wide ◽  
Rational Construction

Gene transcriptional process is random. It occurs in bursts and follows single-molecular kinetics. Intermittent bursts are measured based on their frequency and size. They influence temporal fluctuations in the abundance of total mRNA and proteins by generating distinct transcriptional variations referred to as “noise”. Noisy expression induces uncertainty because the association between transcriptional variation and the extent of gene expression fluctuation is ambiguous. The promoter architecture and remote interference of different cis-regulatory elements are the crucial determinants of noise, which is reflected in phenotypic heterogeneity. An alternative perspective considers that cellular parameters dictating genome-wide transcriptional kinetics follow a universal pattern. Research on noise and systematic perturbations of promoter sequences reinforces that both gene-specific and genome-wide regulation occur across species ranging from bacteria and yeast to animal cells. Thus, deciphering gene-expression noise is essential across different genomics applications. Amidst the mounting conflict, it is imperative to reconsider the scope, progression, and rational construction of diversified viewpoints underlying the origin of the noise. Here, we have established an indication connecting noise, gene expression variations, and bacterial phenotypic variability. This review will enhance the understanding of gene-expression noise in various scientific contexts and applications.

scholarly journals Expression noise facilitates the evolution of gene regulation

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Luise Wolf ◽  
Olin K Silander ◽  
Erik van Nimwegen
Keyword(s):  
Gene Expression ◽  
Gene Regulation ◽  
De Novo ◽  
Low Noise ◽  
Noise Levels ◽  
Gene Expression Noise ◽  
E Coli ◽  
Expression Noise ◽  
Evolution Of Gene Regulation ◽  
Rudimentary Form

Although it is often tacitly assumed that gene regulatory interactions are finely tuned, how accurate gene regulation could evolve from a state without regulation is unclear. Moreover, gene expression noise would seem to impede the evolution of accurate gene regulation, and previous investigations have provided circumstantial evidence that natural selection has acted to lower noise levels. By evolving synthetic Escherichia coli promoters de novo, we here show that, contrary to expectations, promoters exhibit low noise by default. Instead, selection must have acted to increase the noise levels of highly regulated E. coli promoters. We present a general theory of the interplay between gene expression noise and gene regulation that explains these observations. The theory shows that propagation of expression noise from regulators to their targets is not an unwanted side-effect of regulation, but rather acts as a rudimentary form of regulation that facilitates the evolution of more accurate regulation.

scholarly journals Fitness costs of noise in biochemical reaction networks and the evolutionary limits of cellular robustness

2016 ◽  
Author(s):  
J. David Van Dyken
Keyword(s):  
Gene Expression ◽  
Cell Size ◽  
Cell Function ◽  
Noise Control ◽  
Average Rate ◽  
Transcriptional Noise ◽  
Gene Expression Noise ◽  
Expression Noise ◽  
Regulatory Complexity ◽  
Gene Regulatory

ABSTRACTGene expression is inherently noisy, but little is known about whether noise affects cell function or, if so, how and by how much. Here I present a theoretical framework to quantify the fitness costs of gene expression noise and identify the evolutionary and synthetic targets of noise control. I find that gene expression noise reduces fitness by slowing the average rate of nutrient uptake and protein synthesis. This is a direct consequence of the hyperbolic (Michaelis-Menten) kinetics of most biological reactions, which I show cause “hyperbolic filtering”, a process that diminishes both the average rate and noise propagation of stochastic reactions. Interestingly, I find that transcriptional noise directly slows growth by slowing the average translation rate. Perhaps surprisingly, this is the largest fitness cost of transcriptional noise since translation strongly filters mRNA noise, making protein noise largely independent of transcriptional noise, consistent with empirical data. Translation, not transcription, then, is the primary target of protein noise control. Paradoxically, selection for protein-noise control favors increased ribosome-mRNA binding affinity, even though this increases translational bursting. However, I find that the efficacy of selection to suppress noise decays faster than linearly with increasing cell size. This predicts a stark, cell-size-mediated taxonomic divide in selection pressures for noise control: small unicellular species, including most prokaryotes, face fairly strong selection to suppress gene expression noise, whereas larger unicells, including most eukaryotes, experience extremely weak selection. I suggest that this taxonomic discrepancy in selection efficacy contributed to the evolution of greater gene-regulatory complexity in eukaryotes.ARTICLE SUMMARYGene expression is a probabilistic process, resulting in random variation in mRNA and protein abundance among cells called “noise”. Understanding how noise affects cell function is a major problem in biology. Here I present theory demonstrating that gene expression noise slows the average rate of cell division. Furthermore, by modeling stochastic gene expression with non-linearity, I identify novel mechanisms of cellular robustness. However, I find that the cost of noise, and therefore the strength of selection favoring robustness, decays faster than linearly with increasing cell size. This may help explain the vast differences in gene-regulatory complexity between prokaryotes and eukaryotes.

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.

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