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A practical guide to intelligent image-activated cell sorting.

Akihiro Isozaki1, Hideharu Mikami1, Kotaro Hiramatsu1

  • 1Department of Chemistry, The University of Tokyo, Tokyo, Japan.

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|July 7, 2019
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Summary
This summary is machine-generated.

Intelligent image-activated cell sorting (iIACS) offers high-throughput, real-time cell sorting using multidimensional images, surpassing traditional methods. This guide details building and using iIACS for advanced single-cell analysis.

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Area of Science:

  • Biotechnology
  • Cell Biology
  • Bioinformatics

Background:

  • Traditional cell sorting methods like fluorescence-activated cell sorting (FACS) rely on limited fluorescence intensity data.
  • There is a need for advanced cell sorting technologies that can analyze complex cellular features beyond fluorescence.
  • Holistic single-cell analysis requires integrating population, cell, and gene-level data.

Purpose of the Study:

  • To provide a practical guide for designing, building, characterizing, and utilizing intelligent image-activated cell sorting (iIACS) systems.
  • To detail the integration of microscopy, cell focusing, sorting, and deep learning for high-content cell analysis.
  • To enable researchers to implement iIACS for advanced single-cell studies.

Main Methods:

  • Integration of high-throughput microscopy (fluorescence, bright-field) with cell focusing and sorting.
  • Application of deep learning algorithms for real-time intelligent decision-making and actuation.
  • Development of a hybrid software-hardware infrastructure for automated data management and operation.

Main Results:

  • iIACS enables sorting based on multidimensional images, capturing unique spatial, chemical, and morphological traits.
  • The system facilitates high-content sorting, linking population-level, cell-level, and gene-level analyses.
  • A comprehensive guide is presented, covering design parameters, component integration, and system characterization.

Conclusions:

  • iIACS represents a significant advancement over FACS, offering richer data for single-cell analysis.
  • The developed protocol allows experienced research teams to build and deploy an iIACS system within approximately three months.
  • iIACS is poised to become an integral tool for comprehensive single-cell research.