The research grew out of a practical need to study the speed of molecular movement in heart muscle cells. "We are interested in how molecules move inside the cell and that's where the development of this method began," explained Marko Vendelin, head of the Laboratory of Systems Biology at the TalTech Department of Cybernetics. While methods for studying molecular movement already existed, researchers found they came with several limitations.

Cells and the molecules inside them are mostly transparent and invisible to the naked eye. To study them, scientists usually turn to fluorescence microscopy. This involves introducing special fluorescent molecules into the cell. "When you shine light on them, they emit light of a different color. That allows you to get rid of background noise," Vendelin said.

The fluorescent molecule attached to the one under study acts like a beacon, helping to pinpoint its location and track its movement. But this requires a trade-off, since the added fluorescent component can be as large or even larger than the molecule being studied.

"What we add is not small, but it allows us to investigate," Vendelin noted. Inevitably, this extra part can affect the behavior and movement of the molecule of interest, which means results must be analyzed with care.

Fluorescence correlation spectroscopy

The classic method of fluorescence correlation spectroscopy (FCS), developed in the 1970s, has two major drawbacks. First, it is slow. Collecting reliable data requires long measurement times that can last for hours. "Our cells started dying," recalled Marko Vendelin.

The second, and in this case even more important, problem lies in the statistical analysis used in FCS. "All the questions FCS was supposed to answer, it actually could not, because the statistical analysis is wrong," Vendelin said. The issue is so fundamental that it has not received enough attention over the past 50 years. Flawed statistics can lead to false conclusions — for example, researchers may think they have detected two types of molecules moving at different speeds inside a cell, when in fact there is only one.

Looking for a solution to the bottleneck in data collection speed, Vendelin came across an idea presented by an American lab at a scientific conference. Their approach promised measurements five times faster. The method was based on analyzing raw data — the arrival times of photons — directly, instead of first running a statistical analysis. In practice, however, the American solution turned out to be extremely slow and "temperamental." "The doctoral student who had to work with it was starting to think he'd retire before he finished analyzing the data," Vendelin joked.

This prompted researchers at Tallinn University of Technology to take the idea further. They developed a new mathematical approach and wrote code that made analysis much faster. Instead of looking at entire seconds-long data streams at once, they broke them down into shorter phases, analyzing each moment when a molecule entered and exited the measurement point.

To speed up the calculations, the team drew on mathematical operations used in the field of artificial intelligence. "The Americans showed that the problem could be solved; we showed that it can actually be done in practice," Vendelin summed up.

Vendelin considers the method's statistical accuracy its most important achievement. "The breakthrough isn't even that we can measure faster — it's that we can analyze data statistically correctly. We can predict whether there really was one type of molecule or two types — we get the right result," the professor explained. That means many previous FCS-based studies, especially those claiming the existence of multiple types of molecules, should now be reexamined with the new method and a critical eye.

In the name of future medicine

Although developing the new method is a major step forward, it is not the main focus of the Laboratory of Systems Biology. The lab's work centers on studying heart muscle cells: how molecules move within them, how energy production and regulation occur and how diseases affect these processes. Interest in the heart muscle traces back to Vendelin's doctoral research.

Physicists and biologists work side by side in the lab to quantitatively study processes in the heart and other muscles. Asked what kinds of drugs have been developed as a result of their work, Vendelin explained that their role lies elsewhere. "Our job is to do basic research. We need to understand what fundamental processes are actually taking place," the biophysicist stressed.

The lab is part of international networks, such as MetaHeart. Through these, findings from basic research — carried out on mice, rats and even fish — are passed on to those preparing and conducting clinical trials. One standout model the lab uses is the trout heart. "A healthy trout heart is in some ways like a diseased human heart," Vendelin noted, pointing to similarities in the spread of electrical signals. This helps researchers better understand mechanisms that are also critical in human disease.

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