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Raman image-activated cell sorting.

Nao NittaTakanori IinoAkihiro IsozakiMai YamagishiYasutaka KitahamaShinya SakumaYuta SuzukiHiroshi TezukaMinoru OikawaFumihito AraiTakuya AsaiDinghuan DengHideya FukuzawaMisa HaseTomohisa HasunumaTakeshi HayakawaKei HirakiKotaro HiramatsuYu HoshinoMary InabaYuki InoueTakuro ItoMasataka KajikawaHiroshi KarakawaYusuke KasaiYuichi KatoHirofumi KobayashiCheng LeiSatoshi MatsusakaHideharu MikamiAtsuhiro NakagawaKeiji NumataTadataka OtaTakeichiro SekiyaKiyotaka ShibaYoshitaka ShirasakiNobutake SuzukiShunji TanakaShunnosuke UenoHiroshi WataraiTakashi YamanoMasayuki YazawaYusuke YonamineDino Di CarloYoichiroh HosokawaSotaro UemuraTakeaki SugimuraYasuyuki OzekiKeisuke Goda
Published in: Nature communications (2020)
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.
Keyphrases
  • single cell
  • cell therapy
  • single molecule
  • deep learning
  • high resolution
  • mass spectrometry
  • quantum dots
  • cell proliferation
  • cell cycle arrest
  • pi k akt
  • high speed
  • flow cytometry