Raman image-activated cell sorting

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.

Hydrodynamic particle focusing enhanced by femtosecond laser deep grooving at low Reynolds numbers

“…For example, flow cytometry employs two sheath fluids to focus cells for the detection and measurements of physical and chemical characteristics of cells 9 . Moreover, particle focusing has been integrated with other on-chip functional components in microfluidic devices for the manipulation and analysis of different types of synthetic and biological particles, such as micelles, bacteria, microalgae, normal and cancer cells [10][11][12] .A variety of microfluidic techniques have been developed for the focusing of particles, which can be categorized into two groups: active and passive techniques 13 . Active techniques, such as thermophoresis 14 , dielectrophoresis (DEP) 15 , optical trapping 16 and acoustophoresis 17 , apply external forces to achieve particle focusing in microchannels.…”

“…For example, flow cytometry employs two sheath fluids to focus cells for the detection and measurements of physical and chemical characteristics of cells 9 . Moreover, particle focusing has been integrated with other on-chip functional components in microfluidic devices for the manipulation and analysis of different types of synthetic and biological particles, such as micelles, bacteria, microalgae, normal and cancer cells [10][11][12] .…”

High-throughput Raman-activated cell sorting in the fingerprint region

“…Our RACS machine achieved 98% purity and 69% yield for PS selection at 13 eps and 90% purity and 53% yield at 31 eps. Assuming ideal flow focusing, measurement, and sorting, the fundamental limit to purity is determined by the probability that an event contains only one particle or cell 12 . Our results for microbead sorting are compared to this model in Fig.…”

“…On the other hand, RACS machines directly identify target molecules in a label-free manner via Raman spectroscopy, which measures the inelastic scattering of incident photons by characteristic molecular vibrations 11 . To date, FACS technology is well developed, commercialized, and broadly adopted, while RACS is nascent and comprised of a small number of lab-based demonstrations 11,12 .…”

Label-free bone marrow white blood cell classification using refractive index tomograms and deep learning

“…To address this issue, several label-free techniques for identifying blood cells have recently been explored, including multiphoton excitation microscopy (Kim et al 2018; Li et al 2010), Raman microscopy (Nitta et al 2020; Orringer et al 2017; Ramoji et al 2012) and hyperspectral imaging (Ojaghi et al 2020; Verebes et al 2013). Each method exploits the endogenous contrast (e.g., Tryptophan, Raman spectra, chromophores) of a specimen with the objective of visualizing and characterizing it without using exogenous agents; however, these modalities require rather complex optical instruments with demanding system alignments and long data acquisition time.…”