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Updated: Sep 11, 2025
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Live Cell Fluorescence Microscopy to Observe Essential Processes During Microbial Cell Growth
Published on: November 24, 2017
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Fluorescence time-lapse microscopy with automatic cell detection.
Ulderico Wanderlingh1,2, Rosa Musotto3, Angela D'Ascola4
1Department of Mathematics and Computer Sciences, Physical Sciences and Earth Sciences, University of Messina, Viale F. Stagno D'Alcontres 31, 98166 Messina, Italy.
The Review of Scientific Instruments
|August 13, 2025
Summary
This study introduces a low-cost Raspberry Pi fluorescence microscopy system for observing cellular dynamics. It uses novel software for automatic analysis of cellular processes and calcium signals.
Area of Science:
- Biophysics
- Cell Biology
- Microscopy
Background:
- Fluorescence microscopy is crucial for biological, medical, and physical sciences.
- Observing fast and slow cellular processes requires advanced imaging systems.
Purpose of the Study:
- To develop an affordable Raspberry Pi-based epifluorescence microscopy system.
- To enable high-fidelity image acquisition and automated analysis of cellular dynamics.
- To facilitate real-time observation of cellular biophysical research.
Main Methods:
- Utilized a Raspberry Pi with Picamera2 API for RAW image acquisition.
- Implemented a novel Numpy-based algorithm for automatic peak identification in fluorescence images.
- Applied the system to extract temporal calcium signals in cultured astrocytes.
Main Results:
- Achieved high-fidelity image acquisition for cellular processes.
- Successfully detected regions of interest in cellular cultures automatically.
- Enabled precise extraction of temporal calcium signal evolution in astrocytes.
Conclusions:
- The developed system provides an affordable yet powerful solution for cellular biophysical research.
- It enhances accessibility to advanced imaging and analysis capabilities for laboratories.
- Offers robust real-time observation of cellular dynamics and molecular interactions.
