RRC ID 60918
Author Nitta N, Iino T, Isozaki A, Yamagishi M, Kitahama Y, Sakuma S, Suzuki Y, Tezuka H, Oikawa M, Arai F, Asai T, Deng D, Fukuzawa H, Hase M, Hasunuma T, Hayakawa T, Hiraki K, Hiramatsu K, Hoshino Y, Inaba M, Inoue Y, Ito T, Kajikawa M, Karakawa H, Kasai Y, Kato Y, Kobayashi H, Lei C, Matsusaka S, Mikami H, Nakagawa A, Numata K, Ota T, Sekiya T, Shiba K, Shirasaki Y, Suzuki N, Tanaka S, Ueno S, Watarai H, Yamano T, Yazawa M, Yonamine Y, Di Carlo D, Hosokawa Y, Uemura S, Sugimura T, Ozeki Y, Goda K.
Title Raman image-activated cell sorting.
Journal Nat Commun
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.
Volume 11(1)
Pages 3452
Published 2020-7-10
DOI 10.1038/s41467-020-17285-3
PII 10.1038/s41467-020-17285-3
PMID 32651381
PMC PMC7351993
MeSH Animals Cell Separation / methods* Humans Spectrum Analysis, Raman / methods*
IF 12.121
Times Cited 0
Resource
Algae NIES-48 NIES-2293 NIES-2463 NIES-3640