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Quantifying E. coli proteome and transcriptome with single-molecule sensitivity in single cells.

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TLDR
System-wide analyses of protein and mRNA expression in individual cells with single-molecule sensitivity using a newly constructed yellow fluorescent protein fusion library for Escherichia coli found that almost all protein number distributions can be described by the gamma distribution with two fitting parameters which, at low expression levels, have clear physical interpretations as the transcription rate and protein burst size.
Abstract
Protein and messenger RNA (mRNA) copy numbers vary from cell to cell in isogenic bacterial populations. However, these molecules often exist in low copy numbers and are difficult to detect in single cells. We carried out quantitative system-wide analyses of protein and mRNA expression in individual cells with single-molecule sensitivity using a newly constructed yellow fluorescent protein fusion library for Escherichia coli. We found that almost all protein number distributions can be described by the gamma distribution with two fitting parameters which, at low expression levels, have clear physical interpretations as the transcription rate and protein burst size. At high expression levels, the distributions are dominated by extrinsic noise. We found that a single cell's protein and mRNA copy numbers for any given gene are uncorrelated.

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疟原虫var基因转换速率变化导致抗原变异[英]/Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

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Insights into the regulation of protein abundance from proteomic and transcriptomic analyses

TL;DR: Current understanding of the major factors regulating protein expression is summarized to demonstrate a substantial role for regulatory processes occurring after mRNA is made in controlling steady-state protein abundances.
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On the Dependency of Cellular Protein Levels on mRNA Abundance.

TL;DR: It is concluded that transcript levels by themselves are not sufficient to predict protein levels in many scenarios and to thus explain genotype-phenotype relationships and that high-quality data quantifying different levels of gene expression are indispensable for the complete understanding of biological processes.
References
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Journal ArticleDOI

mRNA-Seq whole-transcriptome analysis of a single cell.

TL;DR: A single-cell digital gene expression profiling assay with only a single mouse blastomere is described, which detected the expression of 75% more genes than microarray techniques and identified 1,753 previously unknown splice junctions called by at least 5 reads.
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An efficient recombination system for chromosome engineering in Escherichia coli

TL;DR: A recombination system has been developed for efficient chromosome engineering in Escherichia coli by using electroporated linear DNA using a defective lambda prophage, which will be especially useful for the engineering of large bacterial plasmids such as those from bacterial artificial chromosome libraries.
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Stochastic mRNA Synthesis in Mammalian Cells

TL;DR: The results demonstrate that gene expression in mammalian cells is subject to large, intrinsically random fluctuations and raise questions about how cells are able to function in the face of such noise.
Journal ArticleDOI

Intrinsic and extrinsic contributions to stochasticity in gene expression

TL;DR: It is shown how the total variation in the level of expression of a given gene can be decomposed into its intrinsic and extrinsic components and theoretically that simultaneous measurement of two identical genes per cell enables discrimination of these two types of noise.
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