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 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 Exploring the Changing Landscape of Cell-to-Cell Variation After CTCF Knockdown via Single Cell RNA-seq

2019 ◽  
Author(s):  
Wei Wang ◽  
Gang Ren ◽  
Ni Hong ◽  
Wenfei Jin
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Single Cell ◽  
Zinc Finger ◽  
Ctcf Binding ◽  
Rna Seq ◽  
Expression Noise ◽  
Genome Wide ◽  
Cell Variation ◽  
Variable Genes

Abstract Background: CCCTC-Binding Factor (CTCF), also known as 11-zinc finger protein, participates in many cellular processes, including insulator activity, transcriptional regulation and organization of chromatin architecture. Based on single cell flow cytometry and single cell RNA-FISH analyses, our previous study showed that deletion of CTCF binding site led to a significantly increase of cellular variation of its target gene. However, the effect of CTCF on genome-wide landscape of cell-to-cell variation is unclear. Results: We knocked down CTCF in EL4 cells using shRNA, and conducted single cell RNA-seq on both wild type (WT) cells and CTCF-Knockdown (CTCF-KD) cells using Fluidigm C1 system. Principal component analysis of single cell RNA-seq data showed that WT and CTCF-KD cells concentrated in two different clusters on PC1, indicating gene expression profiles of WT and CTCF-KD cells were systematically different. Interestingly, GO terms including regulation of transcription, DNA binding, Zinc finger and transcription factor binding were significantly enriched in CTCF-KD-specific highly variable genes, indicating tissue-specific genes such as transcription factors were highly sensitive to CTCF level. The dysregulation of transcription factors potentially explain why knockdown of CTCF lead to systematic change of gene expression. In contrast, housekeeping genes such as rRNA processing, DNA repair and tRNA processing were significantly enriched in WT-specific highly variable genes, potentially due to a higher cellular variation of cell activity in WT cells compared to CTCF-KD cells. We further found cellular variation-increased genes were significantly enriched in down-regulated genes, indicating CTCF knockdown simultaneously reduced the expression levels and increased the expression noise of its regulated genes. Conclusions: To our knowledge, this is the first attempt to explore genome-wide landscape of cellular variation after CTCF knockdown. Our study not only advances our understanding of CTCF function in maintaining gene expression and reducing expression noise, but also provides a framework for examining gene function.

scholarly journals Interplay between gene expression noise and regulatory network architecture

2012 ◽  
Vol 28 (5) ◽  
pp. 221-232 ◽  
Author(s):  
Guilhem Chalancon ◽  
Charles N.J. Ravarani ◽  
S. Balaji ◽  
Alfonso Martinez-Arias ◽  
L. Aravind ◽  
...  
Keyword(s):  
Gene Expression ◽  
Regulatory Network ◽  
Network Architecture ◽  
Gene Expression Noise ◽  
Expression Noise

scholarly journals Identification of regulatory network topological units coordinating the genome-wide transcriptional response to glucose in Escherichia coli

2007 ◽  
Vol 7 (1) ◽  
pp. 53 ◽  
Author(s):  
Rosa Gutierrez-Ríos ◽  
Julio A Freyre-Gonzalez ◽  
Osbaldo Resendis ◽  
Julio Collado-Vides ◽  
Milton Saier ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Regulatory Network ◽  
Transcriptional Response ◽  
Genome Wide

scholarly journals Study strategies for long non-coding RNAs and their roles in regulating gene expression

2015 ◽  
Vol 20 (2) ◽  
Author(s):  
Dan Qin ◽  
Cunshuan Xu
Keyword(s):  
Gene Expression ◽  
Regulatory Network ◽  
Experimental Methods ◽  
Study Strategies ◽  
Mechanisms Of Action ◽  
Cellular Processes ◽  
Genome Wide ◽  
A Genome ◽  
Wide Scale ◽  
Non Coding Rnas

AbstractLong non-coding RNAs (lncRNAs) have attracted considerable attention recently due to their involvement in numerous key cellular processes and in the development of various disorders. New high-throughput methods enable their study on a genome-wide scale. Numerous lncRNAs have been identified and characterized as important members of the biological regulatory network, with significant roles in regulating gene expression at the epigenetic, transcriptional and post-transcriptional levels. This paper summarizes the diverse mechanisms of action of these lncRNAs and looks at the study strategies in this field. A major challenge in future study is to establish more effective bioinformatics and experimental methods to explore the functions, detailed mechanisms of action and structures deciding the functional diversity of lncRNAs, since the vast majority remain unresolved.

scholarly journals The nrfA and nirB Nitrite Reductase Operons in Escherichia coli Are Expressed Differently in Response to Nitrate than to Nitrite

2000 ◽  
Vol 182 (20) ◽  
pp. 5813-5822 ◽  
Author(s):  
Henian Wang ◽  
Robert P. Gunsalus
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Nitrite Reductase ◽  
Transcriptional Activation ◽  
Response Regulator ◽  
Physiological Role ◽  
Growth Conditions ◽  
Potent Inducer ◽  
Culture Techniques ◽  
Nitrite Reductase Gene

ABSTRACT Escherichia coli possesses two distinct nitrite reductase enzymes encoded by the nrfA and nirBoperons. The expression of each operon is induced during anaerobic cell growth conditions and is further modulated by the presence of either nitrite or nitrate in the cells' environment. To examine how each operon is expressed at low, intermediate, and high levels of either nitrate or nitrite, anaerobic chemostat culture techniques were employed using nrfA-lacZ and nirB-lacZ reporter fusions. Steady-state gene expression studies revealed a differential pattern of nitrite reductase gene expression where optimalnrfA-lacZ expression occurred only at low to intermediate levels of nitrate and where nirB-lacZ expression was induced only by high nitrate conditions. Under these conditions, the presence of high levels of nitrate suppressed nrfA gene expression. While either NarL or NarP was able to inducenrfA-lacZ expression in response to low levels of nitrate, only NarL could repress at high nitrate levels. The different expression profile for the alternative nitrite reductase operon encoded by nirBDC under high-nitrate conditions was due to transcriptional activation by either NarL or NarP. Neither response regulator could repress nirB expression. Nitrite was also an inducer of nirB and nrfA gene expression, but nitrate was always the more potent inducer by >100-fold. Lastly, since nrfA operon expression is only induced under low-nitrate concentrations, the NrfA enzyme is predicted to have a physiological role only where nitrate (or nitrite) is limiting in the cell environment. In contrast, the nirB nitrite reductase is optimally synthesized only when nitrate or nitrite is in excess of the cell's capacity to consume it. Revised regulatory schemes are presented for NarL and NarP in control of the two operons.

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