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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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Related Experiment Video

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Sorting of Streptomyces Cell Pellets Using a Complex Object Parametric Analyzer and Sorter
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Starch granular size and multi-scale structure determine population patterns in bivariate flow cytometry sorting.

Chuanhao Zhu1, Xudong Zhang2, Renyuan Xu1

  • 1Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, Shaanxi 712100, China.

International Journal of Biological Macromolecules
|January 20, 2023
PubMed
Summary

Flow cytometry sorting reveals how native starch granule size and structure influence population patterns. Understanding these patterns aids in optimizing starch separation techniques for various crops.

Keywords:
Flow cytometryParticle sizePopulation patternsStarch granulesStructural properties

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Area of Science:

  • Agricultural Science
  • Biophysics
  • Food Science

Background:

  • Bivariate flow cytometry (FC) sorting using forward scatter (FSC) and side scatter (SSC) is a novel method for separating starch granules.
  • The precise mechanisms governing starch population patterns in FC, including the number of subgroups (NS) and FSC/SSC distribution, are not fully understood.

Purpose of the Study:

  • To investigate the relationship between the granular size and multi-scale structure of native starches and their resulting FC-dependent population patterns.
  • To elucidate the factors determining the number of subgroups (NS) and FSC/SSC distribution patterns in native starches.

Main Methods:

  • Utilized bivariate flow cytometry (FC) sorting with FSC and SSC to analyze a diverse range of native starches from cereal, pulse, and tuber crops.
  • Correlated granular size, amylose content (AC), amylopectin chain length distribution, lamellar structure, and short-range ordered structure with observed FC population patterns.

Main Results:

  • The number of subgroups (NS) in FC patterns was significantly associated with particle size, AC, amylopectin chain length distribution, lamellar structure, and short-range ordered structure.
  • Starch granular size strongly correlated with both FSC and SSC distribution patterns.
  • The proportion of amylopectin chains with DP 6-12 influenced short-range order and FSC patterns, while AC affected SSC patterns by altering lamellar and short-range order.

Conclusions:

  • Native starch granular size and internal structure are key determinants of FC-dependent population patterns.
  • Amylopectin chain length and amylose content play distinct roles in shaping FSC and SSC distribution patterns, respectively.
  • This research provides insights into the forming mechanism of starch FC population patterns, aiding in the optimization of starch separation and characterization.