For many years, autofluorescence has been regarded as one of the major challenges in flow cytometry. High background signals, nonspecific fluorescence, and difficulties detecting low-abundance markers have led researchers to view it as an unwanted source of noise.
However, the emergence of spectral flow cytometry has completely changed this perspective.
Today, we know that autofluorescence is not always a problem. In many cases, it represents an intrinsic biological signature of specific cell types and tissues, providing valuable information that was previously ignored or discarded.
In this article, we explain what autofluorescence is, why it occurs, when it becomes a challenge, and how spectral flow cytometry allows researchers to transform this apparent «noise» into meaningful biological insight.
Autofluorescence is the natural emission of light by endogenous cellular molecules after excitation with a laser.
Unlike fluorescent dyes or antibody-conjugated fluorochromes, these molecules are naturally present within cells and tissues, producing fluorescence even before any staining procedure is performed.
Some of the most important endogenous fluorophores include:
Each of these molecules exhibits a characteristic emission spectrum, although their signals often overlap with commonly used fluorochromes.
Autofluorescence is not an instrument artifact.
It is a direct consequence of normal cellular biochemistry.
Many molecules involved in cellular metabolism naturally absorb photons and emit fluorescence. In fact, researchers studying cellular metabolism frequently exploit these intrinsic fluorescent properties to investigate metabolic activity without using external probes.
As a result, autofluorescence intensity varies depending on factors such as:
This means that autofluorescence reflects genuine biological information rather than random background.
In conventional flow cytometry, each detector captures only a limited portion of the emitted fluorescence spectrum.
When autofluorescence overlaps with the emission profile of a fluorochrome, it can:
For decades, the standard strategy was therefore to minimize autofluorescence whenever possible.
The introduction of spectral flow cytometry represents one of the most significant technological advances in modern cytometry.
Unlike conventional systems, spectral instruments do not measure fluorescence intensity in isolated channels. Instead, they record the entire emission spectrum generated by each individual event.
Every fluorochrome possesses a unique spectral fingerprint.
Importantly, autofluorescence also has its own characteristic spectral signature.
Using advanced spectral unmixing algorithms, modern software can:
Rather than simply removing background fluorescence, spectral cytometry allows researchers to characterize and exploit it.
One of the most exciting applications of spectral flow cytometry is using autofluorescence as a phenotypic marker.
Several cell populations display highly characteristic autofluorescence patterns that facilitate their identification even before antibody staining.
Examples include:
In these situations, autofluorescence becomes part of the biological phenotype rather than an experimental limitation.
Autofluorescence is particularly relevant in tissues naturally enriched in endogenous fluorophores.
Lung tissue contains abundant elastin, collagen, and especially alveolar macrophages, which exhibit remarkably high autofluorescence.
In conventional flow cytometry, this often complicates the identification of immune cell populations.
By contrast, spectral flow cytometry enables researchers to isolate this signal and use it to improve cell characterization.
The central nervous system represents another classic example.
Aging neurons accumulate lipofuscin, one of the strongest endogenous fluorophores responsible for brain autofluorescence.
In addition, the high metabolic complexity of neural tissue generates distinct autofluorescence profiles across different cell populations.
This has become increasingly valuable in studies of:
Cell dissociation protocols often preserve much of the intrinsic autofluorescence present in solid tissues.
Samples obtained from:
can therefore benefit significantly from spectral flow cytometry, which recovers biological information that would otherwise remain hidden within background fluorescence.
The answer is not necessarily.
The optimal strategy depends on the experimental objectives.
For conventional flow cytometry, minimizing autofluorescence often improves data quality and marker resolution.
However, when using spectral flow cytometry, researchers should consider whether autofluorescence itself contains biologically meaningful information.
Increasingly, laboratories are incorporating autofluorescence into their analytical workflows rather than treating it solely as an unwanted artifact.
When analyzing tissues with elevated autofluorescence, consider the following recommendations:
Technological advances are transforming the way researchers interpret flow cytometry data.
What was once considered an unavoidable limitation is now recognized as a valuable source of biological information related to cellular metabolism, phenotype, and tissue physiology.
Rather than simply removing autofluorescence, spectral flow cytometry identifies, separates, and—when appropriate—leverages it as an additional analytical parameter.
As high-dimensional cytometry continues to evolve, understanding autofluorescence has become an important advantage for researchers working with lung, brain, tumors, and other complex solid tissues.