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Didusch, S.

Publications and source records attributed to Didusch, S..

4 recordsLinked to original sources

RAStoERK: a reference interaction atlas for insights into signaling and disease

The RAS/RAF/MEK/ERK pathway has been extensively studied for its roles in physiology and disease, yet a systems-level view of its interplay with the broader cellular context is lacking, limiting insight into paralog-specific roles, mutation-driven rewiring, and cross-pathway integration. To address this, we simultaneously mapped the interactomes of all pathway components and their activating and inactivating mutations, identifying 2,500 high-confidence interactors, 88% of which previously unreported, and generating a high-confidence, comprehensive reference map of the pathway in resting and activated states. The pathway behaves like a "molecular organism" that connects to other signaling complexes, operates from distinct subcellular sites, and integrates into networks relevant to physiology and disease. Dataset exploration uncovered paralog- and mutation-specific interaction signatures and pathway-level crosstalk, including previously unknown connections to mRNA metabolism and WNT signaling. The interactomes available at RAStoERK.univie.ac.at provide a foundational community resource for unbiased discovery, targeted mechanistic studies, and potential therapeutic exploration. HighlightsO_LIHigh-resolution interactome map of the RAS to ERK pathway in resting and active states C_LIO_LIState-dependent pathway-level interactions with signaling and functional modules C_LIO_LIMutation-driven interactome rewiring and integration into pathophysiological networks C_LIO_LIA resource to discover pathway crosstalk, disease links, and actionable interventions C_LI

molecular biology↗

Pre-mRNA fate decision safeguards the fidelity of the inflammatory response

The fidelity of immune responses depends on a timely controlled and selective mRNA degradation that is largely driven by RNA-binding proteins (RBPs)[1, 2]. It remains unclear whether the selection of an individual mRNA molecule for degradation is governed by stochastic or directed processes. Here, we show that tristetraprolin (TTP, also known as ZFP36), an essential anti-inflammatory RBP[3], destabilizes target mRNAs via a hierarchical molecular assembly. The formation of the assembly strictly relies on the interaction of TTP with RNA. The TTP homolog ZFP36L1 exhibits similar requirements, indicating a broader relevance of this regulatory program. Unexpectedly, the assembly of the cytoplasmic mRNA-destabilization complex is licensed in the nucleus by TTP binding to pre-mRNA, while mature cytoplasmic mRNA does not constitute a de novo TTP target. Hence, the fate of an inflammation-induced mRNA is decided concomitantly with its synthesis. This decision mechanism prevents the translation of superfluous and potentially harmful inflammation mediators, ensuring an efficient cessation of the immune response, irrespective of transcriptional activity.

molecular biology↗

Interplay between PLEKHG3-regulated actin dynamics and lysosomal trafficking in cell motility

Lysosomes are dynamic organelles regulating metabolic signaling by recruiting cytosolic molecules to protein platforms on their limiting membrane. We used proximity labeling to define interactors and vicinal proteins of LAMTOR3, a component of the Ragulator scaffold that controls mTORC1 signaling and lysosome positioning. The screen has yielded several previously unappreciated interactors, including an actin remodeling network. Here, we characterize the RhoGEF PLEKHG3 as a LAMTOR3 vicinal protein colocalizing with peripheral lysosomes and cortical F-actin at focal adhesion sites. Forced peripheral dispersion of lysosomes drives PLEKHG3 accumulation at focal adhesions and decreases protrusive activity in both wild-type and PLEKHG3-deficient cells. Thus, lysosome positioning governs both PLEKHG3 localization and protrusive activity, yet the protrusion changes can occur independently of PLEKHG3.

cell biology↗

amica: an interactive and user-friendly web-platform for the analysis of proteomics data

SummaryQuantitative proteomics has become an increasingly prominent tool in the study of life sciences. A substantial hurdle for many biologists are, however, the intricacies involved in the associated high throughput data analysis. In order to facilitate this task for users with limited background knowledge, we have developed amica, a freely available open-source web-based software that accepts proteomic input files from different sources and provides quality control, differential expression, biological network and over-representation analysis on the basis of minimal user input. Scientists can use amica interactively to compare proteins across multiple groups, create customized output graphics, and ultimately export the results in a tab-separated format that can be shared with collaborators. Availability and ImplementationThe code for the application, input data and documentation can be accessed online at https://github.com/tbaccata/amica and is also incorporated in the web application. A freely available version of amica is available at https://bioapps.maxperutzlabs.ac.at/app/amica.

bioinformatics↗