Publications by authors named "Eduard Hermann"

Single-molecule spectroscopic quantification of protein-protein interactions directly in the organelles of living cells is highly desirable but remains challenging. Bulk methods, such as Förster resonance energy transfer (FRET), currently only give a relative quantification of the strength of protein-protein interactions. Here, we introduce tube scanning fluorescence cross-correlation spectroscopy (tubeSFCCS) for the absolute quantification of diffusion and complex formation of fluorescently labeled molecules in the mitochondrial compartments.

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Bax is a key regulator of apoptosis that mediates the release of cytochrome c to the cytosol via oligomerization in the outer mitochondrial membrane before pore formation. However, the molecular mechanism of Bax assembly and regulation by other Bcl-2 members remains obscure. Here, by analysing the stoichiometry of Bax oligomers at the single-molecule level, we find that Bax binds to the membrane in a monomeric state and then self-assembles in <1 min.

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α-Pore-forming toxins (α-PFTs) are ubiquitous defense tools that kill cells by opening pores in the target cell membrane. Despite their relevance in host/pathogen interactions, very little is known about the pore stoichiometry and assembly pathway leading to membrane permeabilization. Equinatoxin II (EqtII) is a model α-PFT from sea anemone that oligomerizes and forms pores in sphingomyelin-containing membranes.

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Fluorescence correlation spectroscopy (FCS) is a powerful quantitative method to study dynamical properties of biophysical systems. It exploits the temporal autocorrelation of fluorescence intensity fluctuations originating from a tiny volume (~fL). A theoretical model function can be then fitted to the measured auto-correlation curve to obtain physical parameters such as local concentration and diffusion time.

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Motivation: In order to obtain statistically relevant results, the study of membrane effects at the single-vesicle level requires the analysis of several hundreds of giant unilamellar vesicles (GUVs), which becomes a very time-consuming task if carried out manually. Complete and user-friendly software for fast and bias-free automated analysis has not been reported yet.

Results: We developed a framework for the automated detection, tracking and analysis of individual GUVs on digital microscopy images.

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