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<p>The study of bacteria swimming behavior or their interaction with other bacteria or cells requires an efficient and flexible tool for bacteria manipulation. Optical tweezers have been shown to be perfectly adapted for this task. Here we report optical trapping of pathogen <i>Pseudomonas aeruginosa</i> bacteria using optical fiber tweezers with dedicated nanostructured optical fibers. Well-aligned straight chains of up to ten bacteria were observed with optical fiber tips, whereas contactless trapping was realized at distances of 100 and 45 µm for Fresnel lens fibers and TIROFs, respectively. Very efficient trapping at laser powers as low as 3.7 mW was achieved. The bacteria vitality is an important parameter in trapping experiments. Mean square displacement and speed autocorrelation methods were applied to obtain a vitality measure and to classify the free bacteria trajectories into free floating, running, and run-wrap-run categories. The high frame rates of our observation videos allow us to reveal a relation between bacteria speed and bacteria orientation oscillations.</p>

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Optical trapping with nanostructured optical fibers and motility analysis of Pseudomonas aeruginosa

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月8日

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  • Eric Faudry,
  • Jochen Fick

摘要

The study of bacteria swimming behavior or their interaction with other bacteria or cells requires an efficient and flexible tool for bacteria manipulation. Optical tweezers have been shown to be perfectly adapted for this task. Here we report optical trapping of pathogen Pseudomonas aeruginosa bacteria using optical fiber tweezers with dedicated nanostructured optical fibers. Well-aligned straight chains of up to ten bacteria were observed with optical fiber tips, whereas contactless trapping was realized at distances of 100 and 45 µm for Fresnel lens fibers and TIROFs, respectively. Very efficient trapping at laser powers as low as 3.7 mW was achieved. The bacteria vitality is an important parameter in trapping experiments. Mean square displacement and speed autocorrelation methods were applied to obtain a vitality measure and to classify the free bacteria trajectories into free floating, running, and run-wrap-run categories. The high frame rates of our observation videos allow us to reveal a relation between bacteria speed and bacteria orientation oscillations.