Why Understanding The Jablonski Diagram Will Help You Publish Your Flow Cytometry Data

We are all used to interruptions during our working day, from the ping of an email notification to the knock of a fellow researcher who wants to troubleshoot their experiment.

Fortunately, most of these interruptions only last a few minutes. Some past researchers were not so lucky.

Imagine your work being interrupted by a war. Imagine it being interrupted by two wars that you had to fight in.

Alexander Jablonski often had his studies interrupted, not by emails or colleagues, but by war. Jablonski’s work was held up for years due to military service in two wars. First, he served in the war for Polish independence in 1916, then he served again in the Polish-Bolshevik war in 1920.

In 1930, after the wars were over, Jablonski earned his doctorate. His dissertation, entitled “On the influence of the change of wavelengths of excitation light on the fluorescence spectra” laid the foundation for the rest of his career in physics.

A few years later, in 1935, he created what we flow cytometrists call the Jablonski Diagram.

The Jablonski Diagram Explained 

Flow cytometrists use the Jablonski diagram to aid in understanding and explaining the kinetic events of fluorescence.

Fluorescent compounds start at the ground state (S₀) until they are excited by interacting with a photon of light (Step 1). This photon excites the compound, promoting an electon to a higher energy state (S₁’).

As shown in Step 2, some of this energy is lost by emission of heat and other non-radiative processes, leading to the S₁ state.

The final step in the process (Step 3) shows an electron falling back to the ground state while releasing a photon of light. This photon has a lower energy (higher wavelength) than the exciting photon of light.

3 Practical Takeaways From The Jablonski Diagram 

During a flow cytometry experiment, we capture this photon using a photo-multipler tube (PMT).

With knowledge of the filters in front of that PMT, we can assign the signal to a specific fluorochrome in our panel, leading to the identification of the cell of interest.

The Jablonski diagram helps researchers understand several critical factors about the physics of fluorescence, which is critical to designing higher quality experiments and collecting higher quality data that has a better chance of being published.

Here are 3 practical takeaways from the Jablonski diagram…

1. Quantum Yield Helps Determine “Brightness” 

Looking at the Jablonski diagram, you can see that some energy is lost without generating light. In other words, not all of the photons absorbed are released again and therefore will not be measured by your flow cytometer or cell sorter.

The difference between the number of photons absorbed versus the number of photons released for the instrument’s detectors to pick up is called the quantum yield. 

This yield, in part, is what makes some of your fluorochromes “bright” and therefore best used for dim cell markers, or “not-so-bright” and thus better suited for highly expressed cell surface markers.

For example, Phycoerythrin (PE) has a quantum yield of 0.84, meaning that for every 100 photons absorbed, 84 are released just a few femtoseconds later at a longer wavelength. In this case, it’s easy to see why PE is a favorite fluorochrome for use with low-expression markers in multicolor panels.

Everything else being equal, a marker stained with PE will be seen as brighter than one stained with a lower quantum yield dye, such as Cy3, which has a quantum yield of 0.15. 

But, of course, everything else is not equal. Cy3 is in fact excited by a different range of light than PE and in some conditions will absorb more photons than other dyes on the same laser line.

2. The Extinction Coefficient Helps Determine Fluorescence Intensity

Quantum yield is not everything in terms of the brightness of a fluorochrome.

Output is also a component of input. A compound that can absorb more energy at a particular wavelength than another dye, can still be “brighter” and therefore more easily detected by a flow cytometer. This is true even if the compound has a lower quantum yield than the other dye.

Fluorescence intensity at a given wavelength is thought to be proportional to the product of quantum yield and extinction coefficient. 

Compared to fluorescein, with an extinction coefficient of approximately 80,000 cm^-1M^-1, PE and other phycobiliproteins have very large extinction coefficients, some on the order of 2.4 million cm^-1M^-1. These large extinction coefficients and high quantum yield values make phycobiliproteins very attractive fluorochromes.

Quantum dots also have very high extinction coefficients (~2×10⁶ cm^-1M^-1), though they utilize light sources in the violet range and below.

3. The Stokes’ Shift Allows The Use Of All Available Excitation Sources. 

To efficiently use all available excitation sources, flow cytometrists have learned to place multiple dyes on the same laser line. However, this is only possible because of a key characteristic of the Jablonski diagram, the Stokes’ shift.

The Stokes’ shift is routinely visualized in excitation and emission spectra diagrams, such as the diagram below from Life Technologies. This shift is the difference in energy and wavelength represented by (hνEX – hνEM) in the Jablonski diagram.

As the diagram shows, the Stokes’ shift, in concert with your flow cytometer’s optical filters, allows you to separate distinct signals for 4 different fluorochromes using the 488nm blue laser line.

The Jablonski diagram is simple in nature, but powerful in terms of its practical takeaways. Understanding the various characteristics of the diagram, including the quantum yield, extinction coefficient, and Stokes’ shift, will help you design better flow cytometry experiments. Consider these three characteristics when determining your fluorescent dyes and markers for your next experiment. By understanding the fundamentals of fluorescence that Alexander Jablonski laid out after warring many years ago, you’ll increase the quality of your flow cytometry data.

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