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Flow Cytometry

Flow Cytometry

The development of flow cytometry techniques began in 1934 with initial attempts by Andrew Moldavan, a bacteriologist who counted the cells in a flowing capillary system. Moldavan pumped cells through a capillary tube focused under a microscope for visualization. The invention of photometry allowed the measurement of differentially-stained cells, and Louis Kamentsky developed the first multiparameter flow cytometer in 1965 to identify and count the cancer cells in cervical tissue specimens.
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Related Experiment Video

Updated: Dec 6, 2025

Single-cell Analysis of Bacillus subtilis Biofilms Using Fluorescence Microscopy and Flow Cytometry

Single-cell Analysis of Bacillus subtilis Biofilms Using Fluorescence Microscopy and Flow Cytometry

Published on: February 15, 2012

Using fluorescence flow cytometry data for single-cell gene expression analysis in bacteria.

Luca Galbusera^1,2, Gwendoline Bellement-Theroue^1,2, Arantxa Urchueguia^1,2

¹Biozentrum, University of Basel, Basel, Switzerland.

|October 12, 2020

Summary

This summary is machine-generated.

This study introduces methods to improve quantitative analysis of bacterial fluorescence flow cytometry data. We developed techniques to filter debris and correct for noise, enabling more accurate gene expression measurements.

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Last Updated: Dec 6, 2025

Single-cell Analysis of Bacillus subtilis Biofilms Using Fluorescence Microscopy and Flow Cytometry

Single-cell Analysis of Bacillus subtilis Biofilms Using Fluorescence Microscopy and Flow Cytometry

Published on: February 15, 2012

A Fluorescence-based Method to Study Bacterial Gene Regulation in Infected Tissues

A Fluorescence-based Method to Study Bacterial Gene Regulation in Infected Tissues

Published on: February 19, 2019

Flow Cytometric Analysis of Bimolecular Fluorescence Complementation: A High Throughput Quantitative Method to Study Protein-protein Interaction

Flow Cytometric Analysis of Bimolecular Fluorescence Complementation: A High Throughput Quantitative Method to Study Protein-protein Interaction

Published on: August 15, 2013

Area of Science:

Microbiology
Biophysics
Computational Biology

Background:

Fluorescence flow cytometry (FFC) is a high-throughput method for quantifying single-cell gene expression in bacteria.
Lack of standardized protocols hinders accurate analysis of FFC data, leading to potential misinterpretation of biological variability.

Purpose of the Study:

To systematically investigate biases and establish best practices for quantitative analysis of bacterial FFC data.
To develop and validate methods for accurate inference of single-cell expression distributions from FFC measurements.
To provide an open-source tool for researchers to improve their FFC data analysis.

Main Methods:

Comparative analysis of FFC and microscopy data from E. coli strains with fluorescent reporters.
Development of a Bayesian mixture model for debris removal using scattering signals.
Implementation of calibration methods to correct for autofluorescence and shot noise in fluorescence measurements.

Main Results:

A Bayesian model effectively separates viable cells from debris.
Autofluorescence and shot noise significantly impact fluorescence measurements, requiring correction.
Accurate estimation of cell size variability from FFC scatter signals alone is not feasible due to non-linear scaling and shot noise.

Conclusions:

The developed methods enhance the accuracy of single-cell gene expression quantification in bacteria using FFC.
FFC data requires careful correction for technical noise to distinguish from true biological variation.
The open-source R package E-Flow is provided to facilitate rigorous quantitative analysis of bacterial FFC data.