Label-free chemical imaging flow cytometry by high-speed multicolor stimulated Raman scattering.
Yuta SuzukiKoya KobayashiYoshifumi WakisakaDinghuan DengShunji TanakaChun-Jung HuangCheng LeiChia-Wei SunHanqin LiuYasuhiro FujiwakiSangwook LeeAkihiro IsozakiYusuke KasaiTakeshi HayakawaShinya SakumaFumihito AraiKenichi KoizumiHiroshi TezukaMary InabaKei HirakiTakuro ItoMisa HaseSatoshi MatsusakaKiyotaka ShibaKanako SugaMasako NishikawaMasahiro JonaYutaka YatomiYaxiaer YalikunYo TanakaTakeaki SugimuraNao NittaKeisuke GodaYasuyuki OzekiPublished in: Proceedings of the National Academy of Sciences of the United States of America (2019)
Combining the strength of flow cytometry with fluorescence imaging and digital image analysis, imaging flow cytometry is a powerful tool in diverse fields including cancer biology, immunology, drug discovery, microbiology, and metabolic engineering. It enables measurements and statistical analyses of chemical, structural, and morphological phenotypes of numerous living cells to provide systematic insights into biological processes. However, its utility is constrained by its requirement of fluorescent labeling for phenotyping. Here we present label-free chemical imaging flow cytometry to overcome the issue. It builds on a pulse pair-resolved wavelength-switchable Stokes laser for the fastest-to-date multicolor stimulated Raman scattering (SRS) microscopy of fast-flowing cells on a 3D acoustic focusing microfluidic chip, enabling an unprecedented throughput of up to ∼140 cells/s. To show its broad utility, we use the SRS imaging flow cytometry with the aid of deep learning to study the metabolic heterogeneity of microalgal cells and perform marker-free cancer detection in blood.
Keyphrases
- flow cytometry
- label free
- high resolution
- induced apoptosis
- fluorescence imaging
- high speed
- living cells
- cell cycle arrest
- deep learning
- fluorescent probe
- high throughput
- single molecule
- single cell
- oxidative stress
- endoplasmic reticulum stress
- cell death
- machine learning
- atomic force microscopy
- squamous cell
- quantum dots
- young adults