What is spectral flow cytometry?
Spectral flow cytometry is based on many of the fundamental aspects of conventional flow cytometry, but has unique optical collection and analytical capabilities. Traditional flow cytometry optics are designed to direct emitted photons through a series of mirrors and filters into individual photomultiplier tubes (PMTs). Filter sets with defined wavelength ranges are used to separate narrow bands of light to identify single fluorochromes in individual detectors (Figure 1). In biological applications this is critical for associating a particular fluorescence signal with a label or phenotype. However, with spectral flow cytometry the emission spectrum of every fluorescent molecule is captured by a set of detectors or an array of channels, across a defined wavelength range (Figure 1). Every molecule’s fluorescent spectrum can be recognized, recorded as a spectral signature and used as reference in multicolor applications. Spectral unmixing can then be performed, which relies on the discrimination of fluorescence by identifying differences in the overall spectral signatures.
Figure 1. Comparison of a conventional and spectral flow cytometer system. (Top) A conventional flow cytometer relies on a series of band mirrors and filters to segregate light emission into individual detectors. (Bottom) A spectral flow cytometer uses a grating element to separate light into a focusing lens prior to detection. As separating light keeps diverging in space, a collimating lens is often used to parallelize and direct light linearly before reaching a detector. (Figure adapted from Nolan et al. (2013))
On this page:
- Introduction to spectral flow cytometry
- Advantages and disadvantages of spectral flow cytometry
- Comparison of conventional and spectral flow cytometry hardware
- Light dispersion elements in spectral flow cytometry
- Spectral flow cytometry detector arrays
- Compensation versus spectral unmixing
- Spectral flow cytometry controls and autofluorescence removal
- Related content
Introduction to spectral flow cytometry
Spectral analysis coupled with flow cytometry was first demonstrated by Wade et al., by interfacing the fluidics of a flow cytometer with an optical element that spread the light onto a television vidicon detector. Using a polychromatic dispersion element to spread emitted light in front of the detector allowed for full spectral analysis of a population of cells across a portion of the visible light spectrum. Since then different light dispersion and detection technologies have been used in attempts to increase the number of possible parameters that are identifiable in a system. Robinson’s group from Purdue advanced spectral flow cytometry detection by employing an unmixing algorithm, which was coupled with a 32-channel PMT.[2–6] Nolan et al., approached spectral flow cytometry by using a spectrograph, a light dispersion element, and a CCD camera for detection (Figure 1).[7,8] Spectral cytometry systems are increasingly being implemented into biological workflows, and as with any new system the necessary instrument and assay validation needs to take place (see Spectral flow cytometry assays and reagents).
Advantages and disadvantages of spectral flow cytometry
The need to investigate more cellular properties from a single sample has pushed the field of flow cytometry to implement more lasers and detectors in regions of the light spectrum that were previously unused.[9–11] To achieve this, advances in instrumentation and software have successfully combined rapid single-cell analysis with highly sensitive light detection technologies to expand fluorescence-based applications. Additionally, new fluorescent reagents in the ultraviolet, near-ultraviolet and near-infrared regions continue to enable multiparametric flow cytometry capabilities. More lasers and photo detectors allow for the use of more antibodies and reagents, however, this has increased the complexity of experimental design and analysis.
Spectral flow cytometry innovation is helping to overcome some of the barriers that limit the number of detectable parameters. Current spectral flow cytometry instrumentation offers many of the same capabilities as conventional flow cytometry, including single-cell analysis, small particle detection, and multiparametric detection but with some additional advantages, including improved flexibility in reagent selection and the removal of autofluorescence.[2–8, 12–15] Spectral flow cytometry has undeniably expanded the capabilities of researchers to simultaneously investigate a larger number of parameters in their experiment.
Spectral flow cytometry innovation, through university research and development and more recently through commercial channels, still has potential to improve. Limitations in high-parameter experiments can exist when pairing fluorescent readouts or fluorochromes to fit both the needs of the experiment and instrument’s hardware components. Improvements could be realized by taking advantage of analytical capabilities through advanced mathematical unmixing models that exist in related fields of spectroscopy. In many ways the field of spectral flow cytometry is in its infancy, but it is an exciting story that is still evolving and being told. Navigate through the topics below to understand some of the similarities and differences among conventional and spectral flow cytometry hardware, detection, and analysis.
Comparison of conventional and spectral flow cytometry hardware
Similarities in fluidic and laser design
Both conventional (see Molecular Probes School of Fluorescence–Fundamentals of Flow Cytometry) and spectral flow cytometry are capable of multiparametric analysis at the single cell level. Current spectral flow cytometry instrumentation enables this using similar fluidic technologies that are employed by conventional cytometry systems, either by hydrodynamic focusing or through a micro fluidics chip. These systems deliver the sample through a flow cell or chamber where single cells or particles can be aligned prior to laser interrogation (Figure 1). Excitation of an individual event is generally performed by a set of lasers to determine cellular properties relating to size and granularity, and of course, the fluorescence characteristics present.
For all flow cytometry experiments, the ability to combine fluorochromes relies on excitation wavelength properties and the optical configuration of the cytometer. The compatibility of fluorescent combinations in a multiparametric experiment is a direct result of the laser wavelength and emission detection capabilities. Whether conventional or spectral, a single fluorochrome’s emission pattern can be different in a system with spatially offset lasers versus a system with co-linear lasers. Similarly, although co-linear systems exist on both conventional and spectral instrumentation, the compatibility of any two fluorescent molecules may not be consistent for both technologies due to the differences in collection optics.
Differences in optical design
Whether co-linear or spatially offset, spectral flow cytometry instrumentation captures the full emission pattern of a molecule. Spectral detection is made possible by replacing the optical designs of conventional flow cytometry (Figure 1, bottom) with light dispersion elements (see section Light dispersion elements in spectral flow cytometry below), such as prisms or spectrographs. All emitted light spread onto a detector array prior to analysis enables the generation of individual spectral signatures. Measuring the complete spectrum of a molecule allows the instrument to take advantage of all spectral data to distinguish fluorochromes in multicolor experiments. Therefore, rather than identifying fluorescent molecules by using independent detectors to capture a discrete, selected portion of the fluorochrome’s spectrum, the full fluorescence spectra of each molecule is captured and used for discriminating fluorescent molecules.
Light dispersion elements in spectral flow cytometry
Spectral flow cytometry detection and analysis relies on an instrument’s ability to capture, recognize and unmix the fluorescent patterns emitted by a molecule. The light that is transmitted into a detection system is not only influenced by the nature of the fluorescent molecule but is also a result of the optical design. Historically, light dispersing elements have been used to separate bands of light onto a photonic detector. Some dispersion technologies, such as prisms, result in non-linear spreading, while others, such as diffraction gratings, are intended to spread light linearly or equally into the chosen detector (Figure 2, top and bottom).[2–7] Prisms that result in non-linear light dispersion have the advantage of retaining more light through its path to detection. The SP6800 by Sony Biotechnology offers a design based on a series of prisms that bend and separate light into a 32-channel PMT array (depiction in Figure 3). Diffraction grating resulting in linear spreading can improve resolution in some areas of the spectrum and may allow for easier implementation into some systems.[7,8] There are other positive and negative aspects regarding the types of light dispersion optics, which have implications in retention of light, spectral resolution, and the type of mathematical models used for spectral separation and analysis, but are beyond the scope of technical detail discussed here.[7,8,13,14]
Figure 2. A depiction of linear and non-linear spreading. Dispersion elements used in spectral cytometry instrumentation result in non-linear or linear spreading of light. Prisms spread light non-linearly due to their triangular shape, while grating spread lights linearly across the spectrum.
Figure 3. Spectral detection through prism spectroscopy. In this scenario light emission is being separated through a series of prisms. Non-linearly dispersed light is then captured by a 32-channel detector array. This prism array could also be replaced with a spectrograph or other grating elements.
The Cytek Aurora Spectral Analyzer has combined spatially offset lasers with avalanche photodiodes (APDs) for detection of the full spectra. This optical design allows for a single cell to be interrogated by individual lasers each with its own detector array. This technological approach has been successful in resolving some fluorophores that other systems may not be able to. Of course, the appropriate combinations of fluorescent molecules in panel design or multicolor experiments can vary depending on the instrument. Therefore, it is necessary to carefully select reagents that are compatible with both the technology and the biology (see Spectral flow cytometry assays and reagents).
Spectral flow cytometry detector arrays
The use of sensitive photonic detection devices such as charge coupled device (CCD) cameras, multi-anode PMT arrays or an array of APDs have been used with various light dispersive designs for spectral detection.[3–5,7,8] Sensitivity of a photo detector, quantitated as quantum efficiency, is a measurement of the ability of a detector to convert captured photons into photoelectrons. Although, individual PMTs have been a valuable tool in amplifying dim signals into measurable electronic data points, they require broader filter ranges to improve detection of molecules that emit in far-red and near-infrared channels, as those molecules tend to have broader emission spectra with reduced brightness.[7,8,15] In conventional cytometry, this has sometimes limited the combinatorial use of molecules emitting at wavelengths greater than 650 nm. This provides opportunity for improvements in two areas; introducing molecules in the far-red areas of the spectrum that are brighter with narrow wavelengths, and detectors that have higher quantum efficiencies.
In spectral cytometry, dividing the fluorescent spectrum across a 32-channel array of PMTs increases the number of channels as well as the theoretical number of fluorophores that can be used in combination. The Sony SP6800 achieves this with a series of ten prisms to disperse light into a multi-anode PMT detector array (Figure 3 is a depiction of the Sony instrument’s prism dispersion technology) without the need for traditional filter sets to distinguish light. As described previously a prism series will result in minimal loss of light, however a prism will transmit light in a non-linear fashion. Non-linear detection by the PMT array can be corrected through a mathematical algorithm that enables the software to distinguish the spectral profiles.[5,13,16,17]
CCD arrays historically used for spectral imaging have been adopted for use in spectral flow cytometry because of their increased sensitivity and their ability to improve the resolution of far-red and near-infrared emitting molecules.[3,6,7] Additionally, CCD cameras offer faster detection and therefore support higher acquisition speeds and particle detection frequency.[3,6,7] The use of APDs, which also have a higher quantum efficiency than PMTs, is becoming increasingly popular in conventional and spectral flow cytometry systems. On the Cytek Aurora instrument, each laser’s detector array has a set of APDs organized sequentially to separate narrow bands of light (Figure 4). Each array can be used in capturing all the fluorescence of a molecule that is emitted after an excitation source. On the 3-laser system, a violet (405 nm) laser APD array will capture light from ~400–800 nm across 16 discrete individual channels (Figure 4). The principle would repeat itself for a blue (488 nm) laser, capturing light from ~500–850 nm across 14 channels, and a red (633 nm) laser would capture any emission from ~650–850 nm across 8 channels. In this system there are 38 channels or data points for capturing the fluorescent spectral signature.
Figure 4. Example of a violet laser detector module. A 16-detector set module associated with the violet laser separates narrow wavelengths of light using a series of mirrors and filters into individual avalanche photo diodes.
As an example of this, the spectral signature for PerCP-Cyanine5.5 is shown in Figure 5 (bottom panel). This signature is the result of the emission produced by each laser from each array, which is stitched together to produce the overall emission profile (Figure 5 bottom panel). PerCP-Cyanine5.5 has a broad excitation range and is excited by all three lasers within the system. This phenomenon, which is sometimes referred to as cross-laser excitation, can hinder the number of molecules that can be used and analyzed together in conventional cytometry. For instance, the use of PerCP-Cyanine5.5 may increase the complexity of compensation, due to the presence of fluorescence in multiple detectors, including those from different lasers (Figure 5, top row).
Figure 5. Cross-laser excitation of PerCP-Cyanine5.5. (Top) A conventional 3-laser flow cytometer simulation (Thermo Fisher spectra viewer) to demonstrate how long excitation wavelengths will yield emission in multiple detectors. (Bottom) A spectral pattern was generated using a 3-laser spectral cytometer*. Spatially offset lasers (405 nm, 488 nm, 635 nm) were used in order to generate three distinct emission profiles, then when combined yield the overall spectral signature.
In spectral flow cytometry cross-laser excitation can be advantageous for unmixing in some scenarios. In the example above, the resulting overall spectral signature is defined by the fluorescence captured from each detector set. As unmixing relies on minor differences among the overall spectral signatures, there may be emission differences from one laser that enable the deconvolution of similar spectra (see Figure 7 in analysis section). Adding lasers and detector channels will of course change each spectral signature, which will ultimately provide opportunity to introduce more fluorescent molecules into the color palette. As polychromatic experiments grow in complexity, some areas of the spectrum may have a considerable amount of fluorescence in a given detector. As is the case with conventional cytometry, one must consider the overall fluorescence abundance in that channel from other excited molecules. This can affect the resolution among populations due to the influence of spreading from other molecules, and those influencing factors should be understood when designing any cytometry experiment.
Compensation versus spectral unmixing
The one color, one detector paradigm with conventional flow cytometry is limited by broad emission peaks of the available fluorescent molecules. Filters and mirrors that precede the detection device in flow cytometry need to be broad enough to capture enough light for detection, but with a narrow wavelength range to minimize the fluorescence spillover from nearby fluorochromes. Thus, to resolve multiple signals, much of the emission spectrum is disregarded, which could provide valuable information if harnessed appropriately. As spectral flow cytometers capture the emission spectrum of the fluorescent molecule, more fluorescence data become available for methods of deconvolution and analysis among fluorophores. Minor differences among very similar fluorescent molecules that might never effectively be used together in conventional cytometry, such as allophycocyanin (APC) and Alexa Fluor 647 dye, can be easily differentiated on a spatially offset three laser spectral cytometer (Figure 6). The discrimination of these two red emitting fluorophores is based on differences in their overall spectra (as seen by the red boxes in Figure 6) rather than detection in an individual channel.
Figure 6. Comparison of spectral signatures among two compatible fluorochromes. (Top graph) Allophycocyanin (APC) and (Bottom graph) Alexa Fluor 647 dye are compatible when analyzed on a 3-laser spectral flow cytometer*. Although spectrally similar and mainly detected off the red laser, their unique patterns highlighted in the violet and blue channels allow for the molecules to be easily discriminated on a spectral flow cytometer.
As discussed, fluorescent signal compatibility, at least partly, is a consequence of the hardware components. However, like any flow cytometry experiment, successful analysis and interpretation relies not only on knowledge of the instrument, but careful experimental design, and the proper selection of technical and biological controls. In conventional flow cytometry the biological application relies on the presence of a singular fluorescent single, per detector. In polychromatic experiments, a portion of other emission spectra may overlap and fall within the neighboring detectors. Accurate analysis of the fluorescent signal of interest requires that all other fluorescent signals be removed from that detector. This process of compensation mathematically removes the spectral overlap that is captured in secondary and tertiary detectors. In order to calculate how much compensation is needed, single-color control samples must be run with each experiment to determine the fluorescent properties of a single fluorochrome in a given detector.
Spectral flow cytometry analysis, through spectral unmixing, relies on single-stained reference controls for separating fluorescent populations. Reference controls are absolutely critical to identify the individual spectral signatures present within a combination of fluorescent signals in a multicolor experiment (see workflow of a 2-color spectral flow cytometry experiment in Figure 7). To do so, mathematical algorithms, such as the least squares method (LSM) can be used to calculate the contribution of each known fluorescence spectrum to the total collected emission signal.[14,16,17] LSM performs linear unmixing and relies on a consistent noise level among detectors in the system in order to unmix a combination. This approach has enabled spectral instrumentation to reach scientific and commercial value, but there are variabilities in the optics of a system that the least squares method ignores. Other methods including principal component analysis (PCA), probabilistic spectrum analysis (PSA), Karhunen-Loeve transformation, or a combination of them, can help normalize data and improve separation accuracy.[5,7,14,16,17] Improvements in these approaches will help spectral flow cytometry realize its potential and gain capabilities that are not currently available.
Figure 7. A two-color experiment using spectrally similar molecules on a 3-laser spectral flow cytometer*. Isolated PBMCs were prepared for spectral flow cytometry analysis. Individual control samples were first stained with Pacific Orange and eFluor 506 dyes and analyzed for use as reference controls (data not shown). (A) The experimental sample was co-stained with both fluorophores and analyzed prior to unmixing. (B) Linear unmixing is performed using the single-stained reference control data to deconvolute the fluorophores present on the individual molecule. (C) Clear separation of CD4 and CD8 T cells is identified after unmixing. Note: Based on a spillover spread matrix between these two fluorophores (as demonstrated by a 20 color staining spread matrix) there was expected spreading of eFluor 506 dye into the Pacific Orange channel, and for this reason these two fluorophores were chosen to identify mutually exclusive markers.
Spectral flow cytometry controls and autofluorescence removal
Spectral flow cytometry allows for more detectors off a given laser to increase the possible number of fluorescent molecules in a system as long as the number of molecules does not exceed the number of detectors. The same experimental design considerations in conventional flow cytometry also apply to spectral flow cytometry. Cytometrists must continue to practice the fundamentals in panel design and the aspects that affect compatibility among fluorescent molecules. Staining index or brightness, antigen density or expression level of the target, to name a few, are critical considerations when designing multicolor panels. Unstained, single-color reference and fluorescence minus one (FMO) controls need to be used to determine autofluorescence and proper gating of true fluorescent populations.
Autofluorescence can appear across a wide range of the light spectrum, but with varying degrees of intensity and wavelengths due to inherent cellular properties, such as cell size, organelles and various compounds and proteins. As spectral flow cytometers have the ability to identify spectral patterns, autofluorescence determination becomes much simpler. By identifying autofluorescence spectral patterns, spectral flow cytometry instrumentation and software are able remove the autofluorescence signal during unmixing and analysis. Autofluorescence extraction simplifies gating and allows for low-expressing targets or dim levels of fluorescence to be more readily identified (see PrimeFlow RNA example).
Spectral flow cytometry can accommodate the simultaneous use of more reagents off of one laser. However, marrying this concept to polychromatic panels in biology still needs to be carefully approached. No two instruments are the same, and experimental conditions and the factors that influence compatibility of reagents need to be thoroughly considered in the experimental design. Ultimately, spectral flow cytometry has advantages and disadvantages when compared to conventional cytometry, and its uses may be more suitable for different researchers and application areas, but it certainly is growing in adoption and being used in an increasing number of research areas such as cell molecular and cancer biology, immunology, and microbiology.
* All spectral flow cytometry data shown were generated by Cytek Biosciences on a Cytek™ Aurora spectral flow cytometer 3-laser system and analyzed using SpectroFlo™ software.
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- Wade CG, et al. (1979) Spectra of cells in flow cytometry using a vidicon detector. J Histochem Cytochem 27:1049–52.
- Robinson, JP (2004) Multispectral cytometry: The next generation. Biophoton Int 36–40.
- Goddard G, et al. (2006) Single particle high resolution spectral analysis in flow cytometry. Cytometry A 69:842–51.
- Robinson, JP, Grégori, G, Rajwa, B, Jones, J, Patsekin, V. Multispectral detector and analysis system. Purdue University assignee USA patent 72,802,042,007 (2007).
- Gregori G, et al. (2011) Hyperspectral cytometry at the single-cell level using a 32-channel photodetector. Cytometry A 81:35–44.
- Futamura K, et al. (2015) Novel full‐spectral flow cytometry with multiple spectrally‐adjacent fluorescent proteins and fluorochromes and visualization of in vivo cellular movement. Cytometry A 87: 830–842.
- Nolan JP, Condello D (2013) Spectral Flow Cytometry. Curr Protoc Cytom Unit1.27.
- Watson DA, et al. (2008). A flow cytometer for the measurement of Raman spectra. Cytometry A 73:119–28.
- Roederer M, et al. (1997) 8 color, 10-parameter flow cytometry to elucidate complex leukocyte heterogeneity. Cytometry A 29:328–39.
- De Rosa SC, Roederer M (2001) Eleven-color flow cytometry. A powerful tool for elucidation of the complex immune system. Clin Lab Med 21:697–712, vii.
- Perfetto SP, et al. (2004) Seventeen-colour flow cytometry: unraveling the immune system. Nat Rev Immunol 4:648–55.
- Gauci MR, et al. (1996) Observation of single-cell fluorescence spectra in laser flow cytometry. Cytometry 25:388–93.
- Schmutz S, et al. (2016) Spectral cytometry has unique properties allowing multicolor analysis of cell suspensions isolated from solid tissues. PLoS ONE 11.
- Sander CK, Mourant JR (2013) Advantages of full spectrum flow cytometry. J Biomed Opt 18:037004.
- Lawrence GW, et al. (2008) Enhanced Red and Near Infrared Detection in Flow Cytometry Using Avalanche Photodiodes. Cytometry A 73:767–776.
- Feher K, et al. (2016) Multispectral flow cytometry: The consequences of increased light collection. Cytometry A 69:681–689.
- Novo D, et al. (2013) Generalized unmixing model for multispectral flow cytometry utilizing nonsquare compensation matrices. Cytometry A 83A:508–520.
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