Raman Image-activated Cell Sorting

Overview

Journal Nat Commun

Specialty Biology

Date 2020 Jul 12

PMID 32651381

Citations 56

Authors

Nao Nitta

Takanori Iino

Akihiro Isozaki

Mai Yamagishi

Yasutaka Kitahama

Shinya Sakuma

Yuta Suzuki

Hiroshi Tezuka

Minoru Oikawa

Fumihito Arai

Takuya Asai

Dinghuan Deng

Hideya Fukuzawa

Misa Hase

Tomohisa Hasunuma

Takeshi Hayakawa

Kei Hiraki

Kotaro Hiramatsu

Yu Hoshino

Mary Inaba

Yuki Inoue

Takuro Ito

Masataka Kajikawa

Hiroshi Karakawa

Yusuke Kasai

Yuichi Kato

Hirofumi Kobayashi

Cheng Lei

Satoshi Matsusaka

Hideharu Mikami

Atsuhiro Nakagawa

Keiji Numata

Tadataka Ota

Takeichiro Sekiya

Kiyotaka Shiba

Yoshitaka Shirasaki

Nobutake Suzuki

Shunji Tanaka

Shunnosuke Ueno

Hiroshi Watarai

Takashi Yamano

Masayuki Yazawa

Yusuke Yonamine

Dino Di Carlo

Yoichiroh Hosokawa

Sotaro Uemura

Takeaki Sugimura

Yasuyuki Ozeki

Keisuke Goda

Affiliations

Soon will be listed here.

Abstract

The advent of image-activated cell sorting and imaging-based cell picking has advanced our knowledge and exploitation of biological systems in the last decade. Unfortunately, they generally rely on fluorescent labeling for cellular phenotyping, an indirect measure of the molecular landscape in the cell, which has critical limitations. Here we demonstrate Raman image-activated cell sorting by directly probing chemically specific intracellular molecular vibrations via ultrafast multicolor stimulated Raman scattering (SRS) microscopy for cellular phenotyping. Specifically, the technology enables real-time SRS-image-based sorting of single live cells with a throughput of up to ~100 events per second without the need for fluorescent labeling. To show the broad utility of the technology, we show its applicability to diverse cell types and sizes. The technology is highly versatile and holds promise for numerous applications that are previously difficult or undesirable with fluorescence-based technologies.

Citing Articles

Unveiling the Molecular Secrets: A Comprehensive Review of Raman Spectroscopy in Biological Research.

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Transformation gap from research findings to large-scale commercialized products in microfluidic field.

Ma Y, Sun X, Cai Z, Tu M, Wang Y, Ouyang Q Mater Today Bio. 2024; 29:101373.

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High-throughput single-cell sorting by stimulated Raman-activated cell ejection.

Zhang J, Lin H, Xu J, Zhang M, Ge X, Zhang C Sci Adv. 2024; 10(50):eadn6373.

PMID: 39661682 PMC: 11633747. DOI: 10.1126/sciadv.adn6373.

Exploring Microbial Dark Matter for the Discovery of Novel Natural Products: Characteristics, Abundance Challenges and Methods.

Alanzi A J Microbiol Biotechnol. 2024; 35:e2407064.

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Deep Learning-Assisted Label-Free Parallel Cell Sorting with Digital Microfluidics.

Guo Z, Li F, Li H, Zhao M, Liu H, Wang H Adv Sci (Weinh). 2024; 12(1):e2408353.

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