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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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Journal ArticleDOI

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.
Journal ArticleDOI

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

Single-Cell Transcriptional Analysis of Neuronal Progenitors

TL;DR: The technique provides a sensitive and reproducible representation of the single-cell transcriptome and shows that regional differences in gene expression can be predicted from transcriptional analysis of single neuronal precursors isolated by laser capture from defined areas of the developing brain.
Journal ArticleDOI

Random signal fluctuations can reduce random fluctuations in regulated components of chemical regulatory networks.

TL;DR: This work uses chemical master equations to analyze a negative feedback system where species X and S regulate each other's synthesis with standard intracellular kinetics and shows that signal noise can be necessary to reduce X-variation below a Poissonian limit.
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