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A Power-Law Dependence of Bacterial Invasion on Mammalian Host Receptors

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  • Tae J Lee
  • Jeffrey Wong
  • Sena Bae
  • Anna Jisu Lee
  • Allison Lopatkin
  • Fan Yuan
  • Lingchong You

Abstract

Pathogenic bacteria such as Listeria and Yersinia gain initial entry by binding to host target cells and stimulating their internalization. Bacterial uptake entails successive, increasingly strong associations between receptors on the surface of bacteria and hosts. Even with genetically identical cells grown in the same environment, there are vast differences in the number of bacteria entering any given cell. To gain insight into this variability, we examined uptake dynamics of Escherichia coli engineered to express the invasin surface receptor from Yersinia, which enables uptake via mammalian host β1-integrins. Surprisingly, we found that the uptake probability of a single bacterium follows a simple power-law dependence on the concentration of integrins. Furthermore, the value of a power-law parameter depends on the particular host-bacterium pair but not on bacterial concentration. This power-law captures the complex, variable processes underlying bacterial invasion while also enabling differentiation of cell lines.Author Summary: Uptake of bacteria by mammalian cells is highly variable within a population of host cells and between host cell types. A detailed but unwieldy mechanistic model describing individual host-pathogen receptor binding events is captured by a simple power-law dependence on the concentration of the host receptors. The power-law parameters capture characteristics of the host-bacterium pair interaction and can differentiate host cell lines. This study has important implications for understanding the accuracy and precision of therapeutics employing receptor-mediated transport of materials to mammalian hosts.

Suggested Citation

  • Tae J Lee & Jeffrey Wong & Sena Bae & Anna Jisu Lee & Allison Lopatkin & Fan Yuan & Lingchong You, 2015. "A Power-Law Dependence of Bacterial Invasion on Mammalian Host Receptors," PLOS Computational Biology, Public Library of Science, vol. 11(4), pages 1-17, April.
  • Handle: RePEc:plo:pcbi00:1004203
    DOI: 10.1371/journal.pcbi.1004203
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