Shipment tracking for “fat packets” in the body: Researchers at the University of Bonn show that highly sensitive methods can “track” the fat metabolism.
Nothing works in the body without fat: These substances serve as energy suppliers and important building blocks – also for the shells of living cells. Numerous diseases are related to disorders of the lipid metabolism such as obesity or cancer. Researchers at the LIMES Institute at the University of Bonn are now showing how the lipid metabolism down to the individual liver cells of a mouse can be monitored with the greatest sensitivity. This opens up various possibilities, such as minimizing the side effects of new drugs on lipid metabolism. The scientists’ study was published in the journal Nature Methods on October 14, 2019.
Many people think of the padding on their stomach or hips when they hear the term “body fat”. “But no human could survive without lipids, as these substances are called in chemistry,” says Prof. Dr. Christoph Thiele from the LIMES Institute at the University of Bonn. Because fats are important energy stores. For example, if the lipid metabolism is disturbed in cancer patients, this leads to a dramatic weight loss. In addition, lipids often serve as building blocks for the shells of living cells such as brain cells. Therefore, disorders can also lead to neurological diseases.
Scientists are therefore looking for methods that allow them to follow the path from the absorption of fats by the metabolism in the body to excretion using a kind of “tracking” process – similar to a package that can be tracked on the way to its destination . Previously, the researchers used radioactive substances, fluorescent dyes or heavy isotopes of hydrogen-2 (deuterium) to mark the “fat packets”.
“The problem here is that the marked connections cannot be completely differentiated from the unmarked connections,” explains Thiele. This means that only a few marked main compounds can be traced and that this requires very large amounts of substance.
Decay reactions lead to strong signals during the measurement
Together with his teammates Klaus Wunderling and Philipp Leyendecker, the biochemist has now shown how fats in the body of mice can be traced back using a much more sensitive and effective method. They added fatty acids labeled with an additional triple bond called an alkyne group to the mice’s liver cells. The metabolic products then bind to special so-called reporter molecules. In a further step, the compounds collided with gas molecules while their weight was being measured in the mass spectrometer, causing them to break down into certain substances, on which the markings finally became visible. “This decomposition reaction generates very strong signals for the labeled lipids in the mass spectrometer,” said Thiele. This allows a clearer distinction between labeled and unlabeled lipids, and the measurements are about 1000 times more sensitive than conventional methods. It’s also much faster: the results take minutes instead of hours.
“Around 100 different labeled lipids can actually be traced back to individual liver cells,” explains the biochemist. This makes it possible to study in detail both the normal metabolic pathway and pathological deviations. The study of liver cells from mice was an obvious choice for the researchers, as the liver is the “main hub” for lipid metabolism.
However, this method is not yet suitable for experiments on human nutrition. “We still do not know exactly what the fatty acids linked to alkyne groups do in the human body when they are ingested with food,” says Thiele. Nevertheless, the researcher is convinced that this method could be used to study the side effects of drugs on lipid metabolism and possibly to reduce them significantly. Since no consumption experiments on humans are currently possible, the side effects could be tested on cell cultures or organoids. Thiele: “This makes it easy to see how the active ingredients affect fat metabolism.”
Reference: “Multiplex and single cell tracking of lipid metabolism” by Christoph Thiele, Klaus Wunderling and Philipp Leyendecker, October 14, 2019, Nature Methods.
DOI: 10.1038 / s41592-019-0593-6