Literature DB >> 25178355

Single yeast cells vary in transcription activity not in delay time after a metabolic shift.

Anne Schwabe1, Frank J Bruggeman1.   

Abstract

Individual cells respond very differently to changes in environmental conditions. Stochasticity causes cells to respond at different times, magnitudes or both. Here we disentangle and quantify these two sources of heterogeneity. We track the adaptation dynamics of single Saccharomyces cerevisiae cells exposed to a nutrient shift from methionine to sulphate and back. Using single-molecule RNA fluorescence in situ hybridization, we count the number of transcripts of a methionine-biosynthesis enzyme in single cells during adaptation. The variation of response times between cells is small, yet we find a high transient variability in the messenger RNA copy numbers. Surprisingly, single cells display strongly delayed transcription induction, as we could induce transcription fourfold quicker by direct activation and bypassing the cellular control circuitry. Transcription repression occurs rapidly within several minutes. This study indicates that small variability in response timing combined with high, stochastic transcription activity can cause large cell-to-cell variability in dynamic adaptation responses.

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Year:  2014        PMID: 25178355     DOI: 10.1038/ncomms5798

Source DB:  PubMed          Journal:  Nat Commun        ISSN: 2041-1723            Impact factor:   14.919


  12 in total

1.  Single mRNA Molecule Detection in Drosophila.

Authors:  Shawn C Little; Thomas Gregor
Journal:  Methods Mol Biol       Date:  2018

Review 2.  Integrating single-molecule experiments and discrete stochastic models to understand heterogeneous gene transcription dynamics.

Authors:  Brian Munsky; Zachary Fox; Gregor Neuert
Journal:  Methods       Date:  2015-06-12       Impact factor: 3.608

Review 3.  From analog to digital models of gene regulation.

Authors:  Brian Munsky; Gregor Neuert
Journal:  Phys Biol       Date:  2015-06-18       Impact factor: 2.583

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Authors:  David Dickerson; Marek Gierliński; Vijender Singh; Etsushi Kitamura; Graeme Ball; Tomoyuki U Tanaka; Tom Owen-Hughes
Journal:  BMC Cell Biol       Date:  2016-09-08       Impact factor: 4.241

5.  Statistics and simulation of growth of single bacterial cells: illustrations with B. subtilis and E. coli.

Authors:  Johan H van Heerden; Hermannus Kempe; Anne Doerr; Timo Maarleveld; Niclas Nordholt; Frank J Bruggeman
Journal:  Sci Rep       Date:  2017-11-23       Impact factor: 4.379

Review 6.  Taking chances and making mistakes: non-genetic phenotypic heterogeneity and its consequences for surviving in dynamic environments.

Authors:  Coco van Boxtel; Johan H van Heerden; Niclas Nordholt; Phillipp Schmidt; Frank J Bruggeman
Journal:  J R Soc Interface       Date:  2017-07       Impact factor: 4.118

7.  Single-cell study links metabolism with nutrient signaling and reveals sources of variability.

Authors:  Niek Welkenhuysen; Johannes Borgqvist; Mattias Backman; Loubna Bendrioua; Mattias Goksör; Caroline B Adiels; Marija Cvijovic; Stefan Hohmann
Journal:  BMC Syst Biol       Date:  2017-06-05

8.  Effects of growth rate and promoter activity on single-cell protein expression.

Authors:  Niclas Nordholt; Johan van Heerden; Remco Kort; Frank J Bruggeman
Journal:  Sci Rep       Date:  2017-07-24       Impact factor: 4.379

9.  A new protocol for single-cell RNA-seq reveals stochastic gene expression during lag phase in budding yeast.

Authors:  Abbas Jariani; Lieselotte Vermeersch; Bram Cerulus; Gemma Perez-Samper; Karin Voordeckers; Thomas Van Brussel; Bernard Thienpont; Diether Lambrechts; Kevin J Verstrepen
Journal:  Elife       Date:  2020-05-18       Impact factor: 8.140

10.  A mathematical model of cocoa bean fermentation.

Authors:  Mauricio Moreno-Zambrano; Sergio Grimbs; Matthias S Ullrich; Marc-Thorsten Hütt
Journal:  R Soc Open Sci       Date:  2018-10-17       Impact factor: 2.963

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