Draft:Spectral flow cytometry

This page is about the technology. For flow cytometry in general, see Flow cytometry.

Spectral flow cytometry (also: full spectrum flow cytometry) is a type of flow cytometry in which a cytometer collects the full fluorescence emission spectrum of each fluorochrome across multiple detectors rather than measuring discrete bandpass channels. The spectral data are computationally unmixed to determine the contribution of each fluorochrome and cellular autofluorescence, enabling high-parameter immunophenotyping with 30 or more markers per sample.

Terminology

The terms spectral flow cytometry and full spectrum flow cytometry are used interchangeably in the scientific literature. “Full spectrum” emphasizes measurement of the complete emission profile rather than selected optical channels.

History

Early concepts of spectral fluorescence detection in flow cytometry were explored in the 1990s as part of efforts to expand measurable parameters beyond the constraints of filter-based optics. A key technical demonstration was published in 2015, showing that full-spectrum detection could distinguish multiple spectrally overlapping fluorescent proteins and conventional fluorochromes using computational unmixing.

Prototype full-spectrum instruments were later commercialized in the early 2010s, and advances in detector arrays, dispersive optics and unmixing algorithms enabled spectral cytometry to become a major direction in high-dimensional single-cell analysis throughout the 2010s and 2020s.

Principles of operation

Comparison with conventional flow cytometry

Conventional flow cytometry measures fluorescence using narrow bandpass filters. Spectral overlap necessitates compensation and limits multiplexing.

Spectral flow cytometry instead:

• disperses emitted light into tens of narrow spectral bins,
• records a full emission signature across an array of detectors,
• uses computational unmixing to determine fluorochrome contributions.

This approach enables:

• resolution of fluorochromes with highly overlapping spectra,
• improved performance in autofluorescent samples,
• expansion of high-parameter panels beyond conventional limits.

Spectral unmixing

Spectral unmixing models the measured emission as a linear combination of reference spectra for each fluorochrome plus one or more autofluorescence components. Solving this system yields unmixed marker intensities.

Early experimental work demonstrated that full-spectrum acquisition could reliably distinguish multiple fluorescent proteins and conventional fluorochromes using spectral detection and unmixing, validating the feasibility of the method.

Successful unmixing requires:

• accurate and stable reference spectra,
• explicit modeling of autofluorescence,
• quality control to detect spectral drift or detector changes.

Instrumentation

Spectral (full spectrum) cytometers typically employ:

• dispersive optics such as prisms or diffraction gratings,
• multi-channel detector arrays (PMT, APD or CMOS-based),
• software pipelines for spectral unmixing and quality control.

These instruments differ from traditional cytometers in that they do not rely on dedicated filters for each fluorochrome; instead, the entire emission pattern is used for identification.

Optical architecture, number of spectral channels and unmixing algorithms differ by implementation, but share the core concept of full-spectrum acquisition.

Commercial implementations

Several scientific instrument manufacturers have developed spectral (full-spectrum) cytometers. Peer-reviewed reviews describe these systems collectively as a class of high-parameter instruments employing spectral detection and computational unmixing.

Commercially described platforms include:

• spectral detectors with dispersive optics and multi-anode PMTs or APDs,
• instruments with integrated spectral unmixing pipelines,
• spectral cell sorters,
• compact analyzers for routine laboratory workflows.

Published literature references early commercial spectral systems in the 2010s and expanded platforms in the 2020s.

Applications

Spectral flow cytometry is used in:

• immunology and immune profiling,
• oncology and tumor microenvironment analysis,
• cell therapy research including CAR-T,
• infectious disease and inflammation studies,
• high-parameter T- and B-cell immunophenotyping,
• analysis of autofluorescent tissues.

It is commonly integrated with computational workflows such as:

• clustering (FlowSOM, PhenoGraph),
• dimensionality reduction (t-SNE, UMAP),
• machine-learning-based automated gating.

Clinical use

Clinical evaluations have shown that full-spectrum cytometry is promising for:

• diagnostic hematologic immunophenotyping,
• minimal residual disease (MRD) detection,
• immune monitoring,
• extended diagnostic panels with 20–30 or more markers.

Several spectral cytometers have received regulatory approval in clinical laboratories, and spectral unmixing workflows are increasingly being incorporated into diagnostic protocols.

Advantages and limitations

Advantages

• improved resolution of overlapping fluorochromes,
• better handling of autofluorescence,
• reduced reliance on complex filter sets,
• supports high-parameter panels (30+),
• flexible use of lasers and dyes.

Limitations

• requires accurate and stable reference spectra,
• sensitive to spectral drift or optical changes,
• computationally intensive quality control and analysis,
• requires personnel trained in spectral data interpretation.

See also

• Flow cytometry
• Fluorescence spectroscopy
• Single-cell analysis
• Immunophenotyping

External links

• https://pubmed.ncbi.nlm.nih.gov/?term=spectral+flow+cytometry — PubMed search for "spectral flow cytometry"

This page will be placed in the following categories if it is moved to the article namespace.

Categories:

• Flow cytometry
• Laboratory techniques
• Fluorescence