This article describes spectral cytometry, a new approach in flow cytometry that uses the shapes of emission spectra to distinguish fluorochromes. An algorithm replaces compensations and can treat auto-fluorescence as an independent parameter. This new approach allows for the proper analysis of cells isolated from solid organs.
Flow cytometry has been used for the past 40 years to define and analyze the phenotype of lymphoid and other hematopoietic cells. Initially restricted to the analysis of a few fluorochromes, currently there are dozens of different fluorescent dyes, and up to 14-18 different dyes can be combined at a time. However, several limitations still impair the analytical capabilities. Because of the multiplicity of fluorescent probes, data analysis has become increasingly complex due to the need of large, multi-parametric compensation matrices. Moreover, mutant mouse models carrying fluorescent proteins to detect and trace specific cell types in different tissues have become available, so the analysis (by flow cytometry) of auto-fluorescent cell suspensions obtained from solid organs is required. Spectral flow cytometry, which distinguishes the shapes of emission spectra along a wide range of continuous wavelengths, addresses some of these problems. The data is analyzed with an algorithm that replaces compensation matrices and treats auto-fluorescence as an independent parameter. Thus, spectral flow cytometry should be capable of discriminating fluorochromes with similar emission peaks and can provide a multi-parametric analysis without compensation requirements.
This protocol describes the spectral flow cytometry analysis, allowing for a 21-parameter (19 fluorescent probes) characterization and the management of an auto-fluorescent signal, providing high resolution in minor population detection. The results presented here show that spectral flow cytometry presents advantages in the analysis of cell populations from tissues difficult to characterize in conventional flow cytometry, such as the heart and the intestine. Spectral flow cytometry thus demonstrates the multi-parametric analytical capacity of high-performing conventional flow cytometry without the requirement for compensation and enables auto-fluorescence management.
In the last few decades, flow cytometry (FCM) became a widely available analytical method essential for cell phenotyping studies. There has been a substantial increase in the available fluorescent dyes, particularly fluorochromes excited by the violet laser (405 nm) (e.g., Brilliant Violet and new Q-dot dyes). However, the growth of available fluorescent dyes increases the risk of overlapping emissions and requires labor-intensive compensation matrices. FCM became widely used to analyze cell suspensions from solid tissue, but the presence of auto-fluorescent cells limits the discrimination of specifically labeled populations.
The basic principles of spectral FCM are reported in detail in Futamura et al.1,2. Briefly, the spectral FCM used here (see the table of materials) is equipped with 405, 488, and 638 nm lasers. The spectral FCM captures all the emitted fluorescence as spectra in a 32-channel linear array PMT (32ch PMT) for 500 nm to 800 nm and 2 independent PMTs for 420 nm to 440 nm and 450 nm to 469 nm, respectively, which replace the conventional band-pass filters. The 488 and the 405/638 nm laser spots are spatially separated, while the 405 nm and 638 nm laser spots are co-linear. For each individual particle, the spectral FCM measures up to 66 channels of fluorescence data excited by the 405 nm and 488 nm lasers. When cells are excited by the 638 nm laser, the spectral FCM measures 58 channels of fluorescence data because a mask is inserted to prevent the 638 nm laser from shining into the PMT. Spectral FCM analyzes the acquired full spectrum data with an algorithm based on the weighted least squares method (WLSM), which enables the separation of overlapping fluorescent spectra. Spectra derived from single-stained and unstained samples are recognized as the basic reference spectra. Multi-stained samples are mathematically fitted and unmixed, and the spectrum of a sample with mixed fluorescent labels is decomposed into a collection of its constituent spectra. The unmixing, in spectral technology3,4, replaces the compensation that removes the signal from all detectors except the one measuring a given dye.
In this study, we combined and tested 19 fluorochromes in a single, 21-parameter analysis that characterized the major hematopoietic subsets found in the mouse spleen. Additionally, we demonstrated that the spectral cytometry can manage auto-fluorescent signal, thus improving the characterization of intestinal intra-epithelial lymphocytes and of the embryonic heart. Indeed, in these tissues, auto-fluorescence management allowed for the assignment of specific fluorescence to cells that would be excluded from the analysis in conventional FCM.
Conventional FCM is based on the detection of photons emitted after the excitation of fluorescent probes. The fluorescence emission of one fluorochrome detected in a detector designed to measure the signal from another fluorochrome induces physical overlap. This spillover among emission spectra needs to be corrected by compensations.
Spectral FCM and data processing by the unmixing deconvolution algorithm allows for the combination of fluorochromes with close emission peaks without additional …
The authors have nothing to disclose.
We acknowledge the technical and theoretical contributions in spectral cytometry of K. Futamura, who also critically revised the manuscript. We are also indebted to C. Ait-Mansour, P.-H. Commere, A. Bandeira, and P. Pereira for critically reading the manuscript and for endless technical advice and support. We also thank P. Pereira for the gift of the anti Vγ7-APC and Vδ4-Biotin labeled antibodies. We aknowledge the Centre d’Enseignements from Pasteur Institute for welcoming and supporting the filming logistics. This work was supported by the Pasteur Institute, Institut National de la Santé et de la Recherche Médicale (INSERM); the Swiss National Science Foundation and Pasteur Bourse Roux (S.S.); Fundação para a Ciência e a Tecnologia – SFRH/BD/74218/2010 (M.V.); and Université Paris Diderot, the Agence Nationale de la Recherche (ANR) project Twothyme, the ANR, and Program REVIVE (Investment for the Future) (A.C.).
Mice | Janvier Labs | CD45.2 | Source of cells |
Ethanol 70% | VWR | 83801.36 | Sterilization |
DPBS (Ca2+, Mg2+) | GIBCO ThermoFisher | 14040-174 | Embryos collection |
Hanks' Balanced Salt Solution (+Ca2+ +Mg2+) (HBSS+/+) | GIBCO Life ThermoFisher | 14025092 | Dissociation, digestion and staining solutions |
Hanks' Balanced Salt Solution (-Ca2+, -Mg2+) (HBSS-/-) | GIBCO Life ThermoFisher | 14175095 | Dissociation, digestion and staining solutions |
Fetal calf serum (FCS) | EUROBIO | CVFSVF00-0U | Dissociation, digestion and staining solutions |
Collagenase | Sigma | C2139 | Enzymatic solution |
90 x 15 mm, plastic tissue culture Petri dishes. |
TPP | T93100 | Embryos and hearts collection |
35 x 15 mm, plastic tissue culture Petri dishes. |
TPP | T9340 | Hearts collection |
Fine iris scissor | Fine Science Tools | 14090-09 | Dissection tools |
Gross forceps (narrow pattern forceps, curved 12 cm | Fine Science Tools | 11003-12 | Dissection tools |
Fine forceps (Dumont no. 7 forceps, | Fine Science Tools | 11272-30 | Dissection tools |
Scalpel | VWR | 21909-668 | Dissection tools |
LEICA MZ6 Dissection microscope | LEICA | MZ6 10445111 | Sampling; Occular W-Pl10x/23 |
Cold lamp source | SCHOTT VWR | KL1500 compact | Sampling; Two goose neck fibers adapted |
FACS tubes | VWR | 60819-310 | Digesting cells |
96 well plate (round bottom) | VWR | 10861-564 | Staining cells |
Nylon mesh bolting cloth sterilized, 50/50 mm pieces. |
SEFAR NITEX | SEFAR NITEX | Cell filtration |
UltrasComp eBeads | |||
Fluorescence labeled antibodies | Biolegend | Catalogue number see table below | Staining cells |