henhaobio
Sign in

bioRxivBioengineering

A Tailored Approach To Study Legionella Infection Using Lattice Light Sheet Microscope (LLSM)

X. Yi, H. Miao, J. K.-Y. Lo, M. Elsheikh, T.-H. Lee, C. Jiang, Y. Zhang, B. W. Segelke, K. W. Overton, P.-T. Bremer, T. A. Laurence

PDFDOIPreprint

Abstract

Legionella is a genus of ubiquitous environmental pathogens found in freshwater systems, moist soil, and composted materials. More than four decades of Legionella research has provided important insights into Legionella pathogenesis [1]. Although standard commercial microscopes have led to significant advances in understanding Legionella pathogenesis [2,3], great potential exists in the deployment of more advanced imaging techniques to provide additional insights. The Lattice Light Sheet Microscope (LLSM) is a recently developed microscope for 4D live cell imaging with high resolution and minimum photo-damage [4]. We built a LLSM with an improved version for the optical layout with two path-stretching mirror sets and a novel Reconfigurable Galvanometer Scanner (RGS) module to improve the reproducibility and reliability of the alignment and maintenance of the LLSM. We commissioned this LLSM to study Legionella pneumophila infection with a tailored workflow designed over instrumentation, experiments, and data processing methods. Our results indicate that Legionella pneumophila infection is correlated with a series of morphological signatures such as smoothness, migration pattern and polarity both statistically and dynamically. Our work demonstrates the benefits of using LLSM for studying long-term questions in bacterial infection. Our free-for-use modifications and workflow designs on the use of LLSM system contributes to the adoption and promotion of the state-of-the-art LLSM technology for both academic and commercial applications.

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISChen '24Migliori '18Hanrahan '20Chen '25Cheng '25Paniagua '19
63% semantic matchNeuroscience
Yannan Chen, Shradha Chauhan, Cheng Gong+12 more·Nature Biomedical Engineering·Aug 29, 2024· 33 citations