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.

scholarly journals Plasmids for Independently Tunable, Low-Noise Expression of Two Genes

mSphere ◽  
2019 ◽  
Vol 4 (3) ◽  
Author(s):  
João P. N. Silva ◽  
Soraia Vidigal Lopes ◽  
Diogo J. Grilo ◽  
Zach Hensel
Keyword(s):  
Gene Expression ◽  
Protein Expression ◽  
Low Noise ◽  
Expression Systems ◽  
Extrinsic Noise ◽  
Gene Expression Noise ◽  
Expression Noise ◽  
Foreign Proteins ◽  
Noise Limit ◽  
Cell Variation

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 inEscherichia coli. The TetR system was moved to a compatible plasmid backbone, and a system based on thelacrepressor (LacI) was found to also exhibit gene expression noise below the extrinsic noise limit. We characterized gene expression mean and noise across the range of induction levels for these plasmids, applied the LacI system to tune expression for single-molecule mRNA detection under two different growth conditions, and showed that two plasmids can be cotransformed to independently tune expression of two different genes.IMPORTANCEMicrobiologists often express foreign proteins in bacteria in order study them or to use bacteria as a microbial factory. Usually, this requires controlling the number of foreign proteins expressed in each cell, but for many common protein expression systems, it is difficult to “tune” protein expression without large cell-to-cell variation in expression levels (called “noise” in protein expression). This work describes two protein expression systems that can be combined in the same cell, with tunable expression levels and very low protein expression noise. One new system was used to detect single mRNA molecules by fluorescence microscopy, and the two systems were shown to be independent of each other. These protein expression systems may be useful in any experiment or biotechnology application that can be improved with low protein expression noise.

scholarly journals Gene expression noise in a complex artificial toxin expression system

PLoS ONE ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. e0227249
Author(s):  
Alexandra Goetz ◽  
Andreas Mader ◽  
Benedikt von Bronk ◽  
Anna S. Weiss ◽  
Madeleine Opitz
Keyword(s):  
Gene Expression ◽  
Expression System ◽  
Gene Expression Noise ◽  
Expression Noise

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 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.

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.

Estimation of Expression Levels in Spotted Microarrays with Saturated Pixels

2007 ◽  
Vol 6 (1) ◽  
Author(s):  
Chris A Glasbey ◽  
Thorsten Forster ◽  
Peter Ghazal
Keyword(s):  
Gene Expression ◽  
Linear Model ◽  
Principal Components ◽  
Laser Scanning ◽  
Dynamic Range ◽  
Biological Data ◽  
Hyperbolic Model ◽  
Expression Levels ◽  
Biased Estimates ◽  
Gene Expression Levels

Digital images obtained by the laser scanning of spotted microarrays often include saturated pixel values. These arise when the scan settings are sufficiently high and some pixels exceed the limit L=65535 and are instead set to L. Failure to adjust for this censoring leads to biased estimates of gene expression levels. To impute censored values, we propose a linear model based on the principal components of uncensored spots on the same array. This is computationally fast, flexible to adapt to distinctive spot shapes and profiles on different arrays, and is shown to be more effective than the polynomial-hyperbolic model in correcting for the bias. The application to biological data demonstrates the potential for enhancing the dynamic range of detection. Fortran90 subroutines implementing these methods are available at http://www.bioss.ac.uk/~chris.

scholarly journals Use of a Beet necrotic yellow vein virus RNA-5-derived replicon as a new tool for gene expression

2005 ◽  
Vol 86 (2) ◽  
pp. 463-467 ◽  
Author(s):  
Laure Schmidlin ◽  
Didier Link ◽  
Jérôme Mutterer ◽  
Hubert Guilley ◽  
David Gilmer
Keyword(s):  
Gene Expression ◽  
Recombinant Proteins ◽  
Expression System ◽  
Green Fluorescence Protein ◽  
Yellow Vein ◽  
Expression Levels ◽  
Virus Rna ◽  
New Gene ◽  
Infected Cells ◽  
Fluorescence Protein

A new gene-expression system based on RNA-5 of Beet necrotic yellow vein virus (BNYVV) was constructed to allow the expression of recombinant proteins in virally infected cells. Replication and expression levels of the RNA-5-based replicon containing the green fluorescence protein (GFP) gene were compared with those obtained with the well-characterized RNA-3-derived replicon (Rep-3). When RNA-3 and/or RNA-4 BNYVV RNAs were added to the inoculum, the expression levels of RNA-5-encoded GFP were considerably reduced. To a lesser extent, RNA-3-derived GFP expression was also affected by the presence of RNA-4 and -5. Both RNA-3- and RNA-5-derived molecules were able to express proteins within the same infected cells. Together with Rep-3, the RNA-5-derived replicon thus provides a new tool for the co-expression of different recombinant proteins. In Beta macrocarpa, Rep-5-GFP was able to move in systemic tissues in the presence of RNA-3 and thus provides a new expression system that is not restricted to the inoculated leaves.

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.

Sign in / Sign up

Export Citation Format

Share Document