Measuring transcription at a single gene copy reveals hidden drivers of bacterial individuality

Mengyu Wang, Jing Zhang, Heng Xu, Ido Golding

Research output: Contribution to journalLetter

Abstract

Single-cell measurements of mRNA copy numbers inform our understanding of stochastic gene expression1–3, but these measurements coarse-grain over the individual copies of the gene, where transcription and its regulation take place stochastically4,5. Here, we combine single-molecule quantification of mRNA and gene loci to measure the transcriptional activity of an endogenous gene in individual Escherichia coli bacteria. When interpreted using a theoretical model for mRNA dynamics, the single-cell data allow us to obtain the probabilistic rates of promoter switching, transcription initiation and elongation, mRNA release and degradation. Unexpectedly, we find that gene activity can be strongly coupled to the transcriptional state of another copy of the same gene present in the cell, and to the event of gene replication during the bacterial cell cycle. These gene-copy and cell-cycle correlations demonstrate the limits of mapping whole-cell mRNA numbers to the underlying stochastic gene activity and highlight the contribution of previously hidden variables to the observed population heterogeneity.

Original languageEnglish (US)
Pages (from-to)2118-2127
Number of pages10
JournalNature Microbiology
Volume4
Issue number12
DOIs
StatePublished - Dec 1 2019

    Fingerprint

ASJC Scopus subject areas

  • Microbiology
  • Immunology
  • Applied Microbiology and Biotechnology
  • Genetics
  • Microbiology (medical)
  • Cell Biology

Cite this