A Novel Method for Long-Term 3D Tracking of Swimming Bacteria

Clara Chang¹, Ian Magalhães Braga¹, Crisandro Allen Rogel Lazo¹, Keita Kamino^1,2,3*

¹Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan
²Institute of Physics, Academia Sinica, Taipei, Taiwan
³Institute of Physics, National Yang Ming Chiao Tung University, Hsinchu, Taiwan

* Presenter:Keita Kamino, email:kkamino@gate.sinica.edu.tw

Understanding the three-dimensional (3D) motility patterns of bacteria in bulk fluid is crucial for public health research. The analysis of these patterns faces two primary challenges: the stochastic nature of bacterial movement requires extensive data collection to characterize, and non-genetic phenotypic variability prevents reliance on ensemble averaging for statistical analysis. Existing 3D tracking methods provide only short-duration trajectories, typically less than one minute, limiting our ability to quantitatively understand bacterial motility. We address these challenges by introducing a groundbreaking method that tracks individual bacterial cells in bulk fluid for extended periods, exceeding one hour. This presentation will explore the method and the complex motility patterns uncovered by this innovative approach.

Keywords: Bacterial motility, 3D cell tracking, Random walk