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Updated: Dec 15, 2025

A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells

A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells

Published on: August 22, 2025

Raman image-activated cell sorting.

Nao Nitta^1,2,3, Takanori Iino⁴, Akihiro Isozaki^1,5

¹Department of Chemistry, The University of Tokyo, Tokyo, 113-0033, Japan.

Nature Communications

|July 12, 2020

Summary

This summary is machine-generated.

This study introduces Raman image-activated cell sorting, a novel method for cell analysis. It bypasses fluorescent labels by directly detecting molecular vibrations, enabling faster and more versatile cell phenotyping.

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Area of Science:

Biotechnology
Microscopy
Cell Biology

Background:

Image-activated cell sorting (IACS) and imaging-based cell picking have advanced biological studies.
Current methods often rely on fluorescent labeling, which provides indirect molecular information and has limitations.

Purpose of the Study:

To develop a label-free cell sorting technology using Raman spectroscopy.
To enable direct chemical probing of intracellular molecules for cellular phenotyping.

Main Methods:

Demonstration of Raman image-activated cell sorting using ultrafast multicolor stimulated Raman scattering (SRS) microscopy.
Real-time SRS-image-based sorting of single live cells without fluorescent labeling.

Main Results:

Achieved a sorting throughput of up to ~100 events per second.
Showcased applicability to diverse cell types and sizes, highlighting versatility.
Enabled direct probing of chemically specific intracellular molecular vibrations.

Conclusions:

Raman image-activated cell sorting offers a powerful, label-free alternative to fluorescence-based methods.
The technology is highly versatile and suitable for various cell types and sizes.
Holds promise for applications previously challenging for fluorescence-based techniques.