Deregulation of mitotic microtubule (MT) dynamics results in defective spindle assembly and chromosome missegregation, leading further to chromosome instability, a hallmark of tumor cells. RBP-J interacting and tubulin-associated protein (RITA) has been identified as a negative regulator of the Notch signaling pathway. Intriguingly, deregulated RITA is involved in primary hepatocellular carcinoma and other malignant entities. We were interested in the potential molecular mechanisms behind its involvement. We show here that RITA binds to tubulin and localizes to various mitotic MT structures. RITA coats MTs and affects their structures in vitro as well as in vivo. Tumor cell lines deficient of RITA display increased acetylated α-tubulin, enhanced MT stability and reduced MT dynamics, accompanied by multiple mitotic defects, including chromosome misalignment and segregation errors. Re-expression of wild-type RITA, but not RITA Δtub ineffectively binding to tubulin, restores the phenotypes, suggesting that the role of RITA in MT modulation is mediated via its interaction with tubulin. Mechanistically, RITA interacts with tubulin/histone deacetylase 6 (HDAC6) and its suppression decreases the binding of the deacetylase HDAC6 to tubulin/MTs. Furthermore, the mitotic defects and increased MT stability are also observed in RITA mouse embryonic fibroblasts. RITA has thus a novel role in modulating MT dynamics and its deregulation results in erroneous chromosome segregation, one of the major reasons for chromosome instability in tumor cells.
We investigate the influence of different accuracy-detection rate trade-offs on image reconstruction in single molecule localization microscopy. Our main focus is the investigation of image artifacts experienced when using low localization accuracy, especially in the presence of sample drift and inhomogeneous background. In this context we present a newly developed SMLM software termed FIRESTORM which is optimized for high accuracy reconstruction. For our analysis we used in silico SMLM data and compared the reconstructed images to the ground truth data. We observe two discriminable reconstruction populations of which only one shows the desired localization behavior.
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