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Related Experiment Video

Updated: Jul 13, 2025

A Microfluidic Platform for High-throughput Single-cell Isolation and Culture

A Microfluidic Platform for High-throughput Single-cell Isolation and Culture

Published on: June 16, 2016

A live-cell platform to isolate phenotypically defined subpopulations for spatial multi-omic profiling.

Tala O Khatib^1,2,3, Angelica M Amanso^1,2, Christina M Knippler^1,2

¹Department of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, Georgia, United States of America.

|October 11, 2023

Summary

This summary is machine-generated.

A new Spatiotemporal Genomic and Cellular Analysis (SaGA) protocol precisely isolates live cells based on phenotype for multi-omics analysis. This bridges the gap between live-cell behavior and molecular profiles in cellular heterogeneity research.

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Last Updated: Jul 13, 2025

A Microfluidic Platform for High-throughput Single-cell Isolation and Culture

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Area of Science:

Cellular biology
Genomics
Biotechnology

Background:

Existing methods like single-cell RNA sequencing, in situ hybridization, and flow cytometry reveal cellular heterogeneity but cannot link live-cell phenotypes to molecular data.
A critical gap exists in understanding cellular heterogeneity due to the inability to correlate dynamic live-cell phenotypes (e.g., invasiveness, cell interactions) with multi-omic profiles.

Purpose of the Study:

To develop a novel protocol, Spatiotemporal Genomic and Cellular Analysis (SaGA), for the precise isolation and expansion of phenotypically distinct live cells.
To bridge the gap between live-cell phenotypic observation and multi-omics analysis for a comprehensive understanding of cellular heterogeneity.

Main Methods:

The SaGA protocol utilizes cells expressing a photoconvertible fluorescent protein.
Live-cell confocal microscopy is employed to optically highlight specific cells or cell populations exhibiting desired phenotypes.
Fluorescence-activated cell sorting (FACS) is used to isolate these optically marked cells from their microenvironment for subsequent analysis.

Main Results:

SaGA enables the isolation of phenotypically defined live cell subpopulations in a single workday.
Isolated cells can be subjected to multi-omics analysis or expanded for further in vitro/in vivo studies.
The protocol is flexible and adaptable to various research conditions and user-specific interests.

Conclusions:

The SaGA technique provides a powerful method to integrate live-cell phenotypes with multi-omics data, advancing the study of cellular heterogeneity.
This approach facilitates the generation of multi-dimensional datasets crucial for exploring the complex relationships within normal and diseased cellular populations.
SaGA offers a practical and efficient solution for researchers aiming to link cellular behavior to molecular underpinnings.