Spectral flow cytometry

Abstract

Interest in measuring the complete fluorescence spectra of individual cells in flow can be traced to the earliest days of flow cytometry. Recent advances in detectors, optics, and computation have made it possible to make full spectral measurements in the sub-millisecond time frame in which flow cytometry measurements typically occur. This opens up new possibilities for applying spectroscopy to the analysis of individual cells. This unit reviews historical and contemporary approaches to spectral flow cytometry, as well as instrument design, calibration, and data analysis for spectral flow cytometry applications.

Figure 1. Schematic comparison of a conventional and spectral detection in flow cytometry

Conventional detection uses dichroic mirrors and bandpass filters to select colors of light for detection on PMTs. Spectral detection uses gratings or prisms to disperse light across a detector array.

Figure 2. Spectral calibration

Spectra of three different laser lines taken on a grating spectrograph coupled to a CCD detector.

Figure 3. Single particle spectra and virtual band pass filters

A) Spectral flow cytometry data from multifluorphore beads (UltraRainbow, Spherotech). Intensity histograms generated by applying virtual bandpass filters: B) 530/30 C) 585/40, D) 610 LP.

Figure 4. Intensity calibration using single fluorophore calibration beads

A) Spectral flow cytometry data of PE calibration beads (PE Quantibrite, BD Biosciences). B) Histogram of Integrated Emission intensity for the calibration bead set. C) plot of calibration bead MESF value vs Integrated Intensity and the number of photons detected, as calculated from the detector response.

Figure 5. QDot-labeled particles: virtual band pass filters and spectral unmixing

Biotinylated beads labeled with different streptavidin QDots were analyze by spectral flow cytometry. A) Spectra of individual beads B) average particle spectra for each QDot. C) Contribution of each QDot as estimated using band pass filters. D) Contribution of each QDot as estimated using CLS spectral unmixing.

Figure 6. SERS tag-labeled particles: spectral unmixing

Avidin-coated beads labeled with different biotinylated SERS tags were analyze by spectral flow cytometry. A) Spectra of individual beads B) average particle spectra for each SERS tag. C) Contribution of each SERS tag as estimated using CLS spectral unmixing.