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Updated: Jun 26, 2026

Live-Cell Fluorescence Microscopy to Investigate Subcellular Protein Localization and Cell Morphology Changes in Bacteria

Live-Cell Fluorescence Microscopy to Investigate Subcellular Protein Localization and Cell Morphology Changes in Bacteria

Published on: November 23, 2019

Live cell fluorescence microscopy to study microbial pathogenesis.

Adam D Hoppe¹, Stephanie Seveau, Joel A Swanson

¹Department of Chemistry and Biochemistry, South Dakota State University, Brookings, SD 57007-0896, USA. adam.hoppe@sdstate.edu

Cellular Microbiology

|January 13, 2009

Summary

This summary is machine-generated.

Live cell fluorescence microscopy reveals nanometer-scale host-pathogen interactions. This technique offers quantitative insights into cellular and molecular functions for predictive modeling of disease pathways.

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Kinetic Visualization of Single-Cell Interspecies Bacterial Interactions

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Area of Science:

Cell biology
Microbiology
Biochemistry

Background:

Eukaryotic cell and pathogen interactions occur at the nanoscale.
Advances in microscopy and fluorescent probes offer new insights.
Mathematical modeling can enhance understanding of these interactions.

Purpose of the Study:

To review how live cell fluorescence microscopy provides quantitative insights.
To summarize the function of fluorescent probes and imaging devices.
To explore the application of microscopy in studying host-pathogen biochemistry.

Main Methods:

Live cell fluorescence microscopy
Utilizing common imaging instruments
Application of fluorescent probes

Main Results:

Microscopy provides qualitative, quantitative, and predictive descriptions of host-pathogen pathways.
Understanding probe and instrument function is crucial for spatial and temporal analysis.
Quantitative data on cellular and molecular functions of hosts and pathogens can be obtained.

Conclusions:

Live cell fluorescence microscopy is a powerful tool for studying host-pathogen interactions.
Quantitative insights enable a deeper understanding of disease mechanisms.
This approach facilitates predictive modeling of biological pathways.