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Related Concept Videos

Flow Cytometry01:23

Flow Cytometry

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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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Autofluorescence Imaging to Evaluate Red Algae Physiology
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Using Virtual Filtering Approach to Discriminate Microalgae by Spectral Flow Cytometer.

Natasha S Barteneva1,2, Aigul Kussanova3,4, Veronika Dashkova3,5

  • 1School of Sciences and Humanities, Nazarbayev University, Astana, Kazakhstan. natalie.barteneva@nu.edu.kz.

Methods in Molecular Biology (Clifton, N.J.)
|April 19, 2023
PubMed
Summary

Spectral flow cytometry with virtual filters (SFC-VF) effectively identifies marine and freshwater microalgae. This novel method analyzes autofluorescence spectra to differentiate algal taxa in complex samples, aiding phytoplankton bloom monitoring.

Keywords:
CyanobacteriaID7000PhytoplanktonSpectral flow cytometerSpectral flow cytometryVirtual filtering

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Area of Science:

  • Aquatic Ecology
  • Microbiology
  • Analytical Chemistry

Background:

  • Fluorescence methods are crucial for studying marine and freshwater phytoplankton.
  • Distinguishing microalgae populations via autofluorescence analysis presents significant challenges.

Purpose of the Study:

  • To develop a novel approach for identifying and differentiating microalgae populations.
  • To enable quantitative assessment and monitoring of heterogeneous phytoplankton communities at the single-cell level.

Main Methods:

  • Utilized spectral flow cytometry analysis (SFC) with a matrix of virtual filters (VF).
  • Analyzed autofluorescence spectra and light scattering parameters of individual algal cells.
  • Developed a protocol for quantitative assessment and phytoplankton bloom monitoring.

Main Results:

  • Successfully discriminated five major algal taxa based on unique spectral emission fingerprints.
  • Demonstrated the ability to trace specific microalgae taxa in complex laboratory and environmental mixtures.
  • Validated the integrated analysis of spectral fingerprints and light scattering for microalgal differentiation.

Conclusions:

  • The spectral flow cytometry with virtual filtering (SFC-VF) approach offers a robust method for microalgae identification.
  • This technique facilitates the quantitative assessment of heterogeneous phytoplankton communities and aids in phytoplankton bloom detection.