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Bacteria slingshot more on soft surfaces

Author

Listed:
  • Rongrong Zhang

    (Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China)

  • Lei Ni

    (University of Science and Technology of China)

  • Zhenyu Jin

    (Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China)

  • Jiahong Li

    (Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China)

  • Fan Jin

    (Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China
    University of Science and Technology of China
    CAS Key Laboratory of Soft Matter Chemistry, University of Science and Technology of China)

Abstract

Adaptive responses greatly improve the competitive capacities of bacteria in diverse environments. Here, we investigate whether bacteria can adapt to a microenvironment with distinctive softness by examining the type-IV pili (TFP)-mediated motility of Pseudomonas aeruginosa cells on brush-like surfaces that are grafted with a layer of thermally sensitive polymer chains, where the softness of the brush-layer is tunable by applying a small temperature change (from 30 to 37 °C). We report that P. aeruginosa cells slingshot more on soft surfaces at a shear-thinning condition, which greatly facilitates their surface crawling by means of reducing energy dissipation. This adaptive response suggests that P. aeruginosa cells may be able to sense the local viscoelasticity and then deploy TFP to adapt to their physical surroundings.

Suggested Citation

  • Rongrong Zhang & Lei Ni & Zhenyu Jin & Jiahong Li & Fan Jin, 2014. "Bacteria slingshot more on soft surfaces," Nature Communications, Nature, vol. 5(1), pages 1-6, December.
    • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms6541
    DOI: 10.1038/ncomms6541
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    Cited by:

    1. Daniel L Barton & Yow-Ren Chang & William Ducker & Jure Dobnikar, 2024. "Data–driven modelling makes quantitative predictions regarding bacteria surface motility," PLOS Computational Biology, Public Library of Science, vol. 20(5), pages 1-27, May.

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