Single-cell measurements of mRNA copy numbers inform our understanding of stochastic gene expression1,2,3, 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.
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The data that support the findings of this study are available from the corresponding author on request.
The custom MATLAB routines used for processing and analysing the fluorescence microscopy data are freely available from the corresponding author on request.
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We are grateful to the following people for their generous advice and for providing reagents: D. Bates, J. Elf, H. Garcia, M. Girard, J. Halliday, C. Herman, M. Joshi, D. Magnan, J. Moffitt, E. Nudler, R. Phillips, A. Sarrion-Perdigones, S. Sebastian, L. Sepúlveda, A. Singh, P. Sivaramakrishnan, S. Skinner, A. Sokac, J. Tabor, K. Venken and all the members of the Golding lab. Work in the Golding lab is supported by grants from the National Institutes of Health (grant no. R01 GM082837), the National Science Foundation (grant nos. PHY 1147498, PHY 1430124 and PHY 1427654), the Welch Foundation (grant no. Q-1759) and the John S. Dunn Foundation (Collaborative Research Award). H.X. was supported by the Burroughs Wellcome Fund Career Award at the Scientific Interface (grant no. 1013907), the Thousand Talents Plan of China (Programme for Young Professionals), the National Natural Science Foundation of China (grant no. 11774225), the National Key Research and Development Programme of China (grant no. 2018YFC0310800) and the National Science Foundation of Shanghai (grant no. 18ZR1419800). We gratefully acknowledge the computing resources provided by the CIBR Center of the Baylor College of Medicine.
The authors declare no competing interests.
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Wang, M., Zhang, J., Xu, H. et al. Measuring transcription at a single gene copy reveals hidden drivers of bacterial individuality. Nat Microbiol 4, 2118–2127 (2019). https://doi.org/10.1038/s41564-019-0553-z
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