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Reber, S.

Publications and source records attributed to Reber, S..

20 records · Page 2Linked to original sources

FUS-dependent phase separation initiates double-strand break repair

RNA-binding proteins (RBPs) are emerging as important effectors of the cellular DNA damage response (DDR). The RBP FUS is implicated in RNA metabolism and DNA repair, and it undergoes reversible liquid-liquid phase separation (LLPS) in vitro. Here, we demonstrate that FUS-dependent LLPS is necessary for the initiation of the DDR. Using laser microirradiation in FUS-knockout cells, we show that FUS is required for the recruitment to DNA damage sites of the DDR factors KU80, NBS1, 53BP1, and of SFPQ, another RBP implicated in the DDR. The relocation of KU80, NBS1, and SFPQ is similarly impaired by LLPS inhibitors, or LLPS-deficient FUS variants. We also show that LLPS is necessary for efficient {gamma}H2AX foci formation. Finally, using super-resolution structured illumination microscopy, we demonstrate that the absence of FUS impairs the proper arrangement of {gamma}H2AX nano-foci into higher-order clusters. These findings demonstrate the early requirement for FUS-dependent LLPS in the activation of the DDR and the proper assembly of DSBs repair complexes.

molecular biology↗

MTrack: Automated Detection, Tracking, and Analysis of Dynamic Microtubules

Microtubules are polar, dynamic filaments fundamental to many cellular processes. In vitro reconstitution approaches with purified tubulin are essential to elucidate different aspects of microtubule behavior. To date, deriving data from fluorescence microscopy images by manually creating and analyzing kymographs is still commonplace. Here, we present MTrack, implemented as a plug-in for the open-source platform Fiji, which automatically identifies and tracks dynamic microtubules with sub-pixel resolution using advanced objection recognition. MTrack provides automatic data interpretation yielding relevant parameters of microtubule dynamic instability together with population statistics. The application of our software produces unbiased and comparable quantitative datasets in a fully automated fashion. This helps the experimentalist to achieve higher reproducibility at higher throughput on a user-friendly platform. We use simulated data and real data to benchmark our algorithm and show that it reliably detects, tracks, and analyzes dynamic microtubules and achieves sub-pixel precision even at low signal-to-noise ratios.

biophysics↗