Machine learning-based motion tracking reveals an inverse correlation between adhesivity and surface motility of the leptospirosis spirochete

This research investigated bacterial motility over cultured animal cells without using any cellular labeling, such as fluorescent probes. The label-free motion tracking was achieved by the machine learning-based background subtraction method. The shared data set includes the raw tracking data of individual bacterial locomotion (swimming in liquid phase and crawling on cell surfaces of zoonotic spirochete <i>Leptospira interrogans</i>) measured in this study.

本研究针对培养的动物细胞表面的细菌运动能力展开探究，未使用荧光探针等任何细胞标记手段。本研究采用基于机器学习的背景扣除法，实现了无标记运动追踪。本公开数据集包含本研究测得的单株细菌运动原始追踪数据，涵盖人畜共患螺旋体问号钩端螺旋体（Leptospira interrogans）在液相中的游动以及在细胞表面的爬行行为。