The figures show part of a frozen mammalian cell. On the left is a section from the 3D X-ray tomogram (scale: 2 μm). The right figure shows the reconstructed cell volume after applying the new algorithm.

X-ray microscopy at HZB enables high-resolution insights into the interior of cells

X-ray microscopy (cryo-SXT) enables high-resolution insights into the interior of cells and cell organelles - in three dimensions. Until now, the 3D data sets were analyzed manually, which was time-consuming. Now, a team at Freie Universität Berlin has developed an algorithm based on a "folded" neural network. With experts from cell biology (FU Berlin) and X-ray microscopy at Helmholtz Zentrum Berlin, this algorithm has now been used for the first time to analyze cell components in cryo-SXT datasets and was able to identify cell organelles and produce highly detailed, complex 3D images within a few minutes.

Cell examination without complex preparations

With the highly brilliant X-ray light from BESSY II, microscopy images with spatial resolution down to a few tens of nanometers can be produced. Whole cell volumes can be examined without the need for complex sample preparation as in electron microscopy. Under the X-ray microscope, the tiny cell organelles with their fine structures and boundary membranes appear clearly and in detail, even in three dimensions. Therefore, cryo X-ray tomography is ideally suited to investigate changes in cell structures caused, for example, by external triggers. However, the analysis of 3D tomograms has so far required largely manual and labor-intensive data analysis. To overcome this problem, teams led by computer scientist Prof. Dr. Frank Noé and cell biologist Prof. Dr. Helge Ewers (both from Freie Universität Berlin) have now collaborated with the X-ray Microscopy Department at HZB. In the process, the computer science team developed a novel, self-learning algorithm. This AI-based analysis method is based on the automated detection of subcellular structures and accelerates the quantitative analysis of the 3D X-ray data sets. The acquisition of the 3D images to study the interior of biological samples was performed at the U41 beamline at BESSY II.

"In this study, we have now shown how well AI-assisted analysis of cell volumes works, using mammalian cells from cell cultures that have so-called filopodia," says Dr. Stephan Werner, an expert in X-ray microscopy at HZB. Mammalian cells have a complex structure with many different cell organelles, each of which must fulfill different cellular functions. Filopodia are protrusions of the cell membrane and serve in particular for cell migration. "For cryo X-ray microscopy, the cell samples are first snap-frozen, so quickly that no ice crystals form inside the cell. As a result, the cells are in an almost natural state and we can study the structural influence of external factors inside the cell," Werner explains.

"Our work has already aroused considerable interest among experts," says first author Michael Dyhr from Freie Universität Berlin. The neural network correctly recognizes about 70% of the available cell features within a very short time, thus enabling a very rapid evaluation of the data set.

"In perspective, we could use this new analysis method to investigate how cells react to environmental influences such as nanoparticles, viruses or carcinogens much faster and more reliably than before," says Dyhr.

The future is light

With a history going back 200 years in optical technology, its strong scientific foundation and the high number of specialized companies, the capital region is one of Europe’s leading locations in optics, photonics and microsystem technology. In its role as an interface between various technologies, the region often forms the basis for innovative products and services, e.g. in medical and sensory technology or energy and communication technology.

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Source: Helmholtz Zentrum Berlin "Röntgenmikroskopie am HZB ermöglicht hochaufgelöste Einblicke in das Innere von Zellen", 07|18|2023