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Anti-correlation of LacI association and dissociation rates observed in living cells

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Listed:
  • Vinodh Kandavalli

    (Uppsala University)

  • Spartak Zikrin

    (Uppsala University)

  • Johan Elf

    (Uppsala University)

  • Daniel Jones

    (Uppsala University)

Abstract

The rate at which transcription factors (TFs) bind their cognate sites has long been assumed to be limited by diffusion, and thus independent of binding site sequence. Here, we systematically test this assumption using cell-to-cell variability in gene expression as a window into the in vivo association and dissociation kinetics of the model transcription factor LacI. Using a stochastic model of the relationship between gene expression variability and binding kinetics, we performed single-cell gene expression measurements to infer association and dissociation rates for a set of 35 different LacI binding sites. We found that both association and dissociation rates differed significantly between binding sites, and moreover observed a clear anticorrelation between these rates across varying binding site strengths. These results contradict the long-standing hypothesis that TF binding site strength is primarily dictated by the dissociation rate, but may confer the evolutionary advantage that TFs do not get stuck in near-operator sequences while searching.

Suggested Citation

  • Vinodh Kandavalli & Spartak Zikrin & Johan Elf & Daniel Jones, 2025. "Anti-correlation of LacI association and dissociation rates observed in living cells," Nature Communications, Nature, vol. 16(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-56053-z
    DOI: 10.1038/s41467-025-56053-z
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    References listed on IDEAS

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    1. Sora Yang & Seunghyeon Kim & Yu Rim Lim & Cheolhee Kim & Hyeong Jeon An & Ji-Hyun Kim & Jaeyoung Sung & Nam Ki Lee, 2014. "Contribution of RNA polymerase concentration variation to protein expression noise," Nature Communications, Nature, vol. 5(1), pages 1-9, December.
    2. Muir Morrison & Manuel Razo-Mejia & Rob Phillips, 2021. "Reconciling kinetic and thermodynamic models of bacterial transcription," PLOS Computational Biology, Public Library of Science, vol. 17(1), pages 1-30, January.
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