Autofluorescence Flow Cytometry: Insights, Causes, and Impact

Flow cytometry is a powerful tool for analyzing cellular properties, but autofluorescence can complicate data interpretation. This natural emission of light from cells can obscure signals from fluorescent markers, making it difficult to distinguish specific populations or accurately quantify fluorescence intensity.

Understanding the sources and characteristics of autofluorescence is essential for improving experimental accuracy. Researchers must account for variations among cell types, excitation wavelengths, and other influencing factors to minimize its impact on results.

Biochemical Basis Of Cellular Autofluorescence

Autofluorescence arises from the intrinsic fluorescence of cellular components, primarily endogenous fluorophores. These molecules absorb light at specific wavelengths and emit fluorescence without external labeling. Key contributors include nicotinamide adenine dinucleotide (NADH), flavin adenine dinucleotide (FAD), lipofuscin, and porphyrins, each with distinct excitation and emission properties. Their relative abundance and distribution vary across cell types and physiological states, influencing autofluorescence intensity.

NADH and FAD, both involved in cellular metabolism, significantly contribute to autofluorescence. NADH fluoresces in its reduced form, with peak excitation around 340 nm and emission near 460 nm, while FAD emits in its oxidized state, with excitation at approximately 450 nm and emission around 520 nm. The balance between these fluorophores reflects metabolic activity, with shifts in their fluorescence ratios indicating changes in cellular respiration or disease states such as cancer. Highly proliferative cells, including tumor cells, often exhibit altered NADH/FAD fluorescence due to metabolic reprogramming, increasing background signal.

Lipofuscin, an aggregate of oxidized proteins and lipids, accumulates over time, particularly in post-mitotic or senescent cells. This pigment fluoresces across a broad spectrum, from ultraviolet to near-infrared wavelengths. Its presence is especially pronounced in aging cells and tissues under oxidative stress, such as neurons and macrophages, complicating the detection of fluorescent markers in flow cytometry.

Porphyrins, involved in heme biosynthesis, fluoresce strongly in the red spectrum, with excitation peaks around 400 nm and emission near 600 nm. Cells with dysregulated heme metabolism, such as those affected by porphyria or certain malignancies, can exhibit heightened autofluorescence due to porphyrin accumulation. While this property has been used in fluorescence-based cancer detection, it also interferes with fluorophores emitting in similar spectral regions.

Variation Of Autofluorescence By Cell Type

Autofluorescence varies across cell types due to differences in metabolism, pigment accumulation, and structural composition. Epithelial cells often exhibit high autofluorescence from flavin-containing enzymes and metabolic cofactors such as NADH and FAD. Mucosal epithelial cells also contain keratin and other structural proteins that contribute to background fluorescence, complicating the detection of fluorescent markers.

Fibroblasts, central to extracellular matrix production and wound healing, display moderate autofluorescence influenced by mitochondrial activity. They rely heavily on oxidative phosphorylation, and fibroblasts from aged or diseased tissues can accumulate lipofuscin, increasing autofluorescence in the red and near-infrared regions. This is particularly relevant in studies on fibrosis and aging.

Neuronal cells, due to their post-mitotic nature and high oxidative metabolism, are among the most autofluorescent. Lipofuscin accumulation, a hallmark of aging neurons, contributes to persistent fluorescence across a broad spectrum. High levels of flavoproteins and porphyrins further enhance their intrinsic fluorescence, which can obscure signals from exogenous fluorophores in flow cytometry studies of neural tissues. Spectral compensation or autofluorescence subtraction is often necessary for improved signal resolution.

Macrophages and other phagocytic cells also exhibit pronounced autofluorescence due to their role in engulfing and degrading cellular debris. Internalized lipofuscin, oxidized lipids, and metabolic cofactors produce broad-spectrum fluorescence, interfering with fluorophore-labeled antibodies. This is particularly relevant in inflammation-related studies, where activated macrophages display heightened metabolic activity and increased autofluorescence.

Role Of Excitation And Emission Spectra

Excitation and emission spectra play a crucial role in autofluorescence, influencing its intensity and detectability. Each endogenous fluorophore absorbs light at characteristic wavelengths based on its molecular structure. When excited, these molecules emit fluorescence at a longer wavelength due to energy loss during relaxation. The degree of spectral overlap between autofluorescent molecules and fluorophore-labeled probes dictates the extent of interference.

Excitation wavelength selection is key to minimizing background fluorescence. Many endogenous fluorophores, such as NADH and FAD, absorb strongly in the ultraviolet and blue regions. Using excitation sources in these ranges can amplify autofluorescence, reducing contrast between labeled and unlabeled cells. Longer excitation wavelengths, such as red or near-infrared, excite fewer endogenous fluorophores, improving specificity for exogenous labels. This principle is applied in multicolor flow cytometry, where fluorophores emitting in the far-red and near-infrared regions are preferred to minimize spectral interference.

Broad emission profiles of endogenous fluorophores further complicate autofluorescence management. Unlike synthetic dyes engineered for narrow emission peaks, cellular autofluorescence spans multiple spectral regions, increasing the likelihood of overlap with commonly used fluorophores. For example, lipofuscin emits across green to red wavelengths, making it particularly problematic when analyzing fluorophores such as fluorescein isothiocyanate (FITC) or phycoerythrin (PE). This broad emission can lead to spillover into multiple detection channels, requiring compensation techniques or spectral unmixing algorithms to distinguish signals.

Identifying Autofluorescent Signals In Flow Cytometry

Distinguishing autofluorescence from specific fluorescent markers requires a strategic approach. Background fluorescence can obscure true signals, leading to misinterpretation. Analyzing unstained control samples provides a baseline measure of intrinsic fluorescence under the same excitation conditions as the experiment. Comparing these controls to stained samples helps determine whether observed signals originate from endogenous fluorescence or fluorophore-labeled markers.

Fluorescence-minus-one (FMO) controls are useful for detecting autofluorescence. These controls involve staining cells with all fluorophores except the one being analyzed, allowing researchers to assess background signal in the specific channel of interest. If significant fluorescence is detected in the absence of the targeted fluorophore, autofluorescence is a contributing factor. This method is particularly valuable when working with highly autofluorescent cell types, where spillover into multiple detection channels complicates compensation calculations.

Factors That Increase Autofluorescence

Several biological and experimental conditions enhance autofluorescence, complicating flow cytometry analyses. Cellular metabolism is a major contributor, as shifts in metabolic activity alter the abundance and fluorescence intensity of endogenous fluorophores like NADH and FAD. Highly proliferative cells, including cancerous populations, often exhibit increased autofluorescence due to elevated metabolic demands and mitochondrial activity. Similarly, cells undergoing oxidative stress produce more reactive oxygen species, leading to the accumulation of oxidized fluorophores like lipofuscin, which emits broad-spectrum fluorescence.

Fixation and staining protocols can also amplify autofluorescence, particularly with aldehyde-based fixatives such as formaldehyde or glutaraldehyde. These chemicals create protein cross-links that introduce additional fluorescence, particularly in the green to red spectral regions. Prolonged fixation exacerbates this effect, making it important to optimize fixation times and concentrations. Additionally, certain fluorophore-conjugated antibodies may interact with autofluorescent cellular components, complicating signal resolution. Researchers can minimize these issues by incorporating autofluorescence compensation techniques, using alternative fixatives, or employing spectral unmixing methods to separate true fluorescence from background noise.