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Wagner, U.

Publications and source records attributed to Wagner, U..

4 recordsLinked to original sources

TDP-43 oligomerization and RNA binding are codependent but their loss elicits distinct pathologies

Aggregation of the RNA-binding protein TDP-43 is the main common neuropathological feature of TDP-43 proteinopathies. In physiological conditions, TDP-43 is predominantly nuclear and contained in biomolecular condensates formed via liquid-liquid phase separation (LLPS). However, in disease, TDP-43 is depleted from these compartments and forms cytoplasmic or, sometimes, intranuclear inclusions. How TDP-43 transitions from physiological to pathological states remains poorly understood. Here, we show that self-oligomerization and RNA binding cooperatively govern TDP-43 stability, functionality, LLPS and cellular localization. Importantly, our data reveal that TDP-43 oligomerization is connected to, and conformationally modulated by, RNA binding. Mimicking the impaired proteasomal activity observed in patients, we found that TDP-43 forms nuclear aggregates via LLPS and cytoplasmic aggregates via aggresome formation. The favored aggregation pathway depended on the TDP-43 state -monomeric/oligomeric, RNA-bound/-unbound- and the subcellular environment -nucleus/cytoplasm. Our work unravels the origins of heterogeneous pathological species occurring in TDP-43 proteinopathies.

cell biology↗

Proteogenomic heterogeneity of localized human prostate cancer progression

BackgroundTumor-specific genomic aberrations are routinely determined by high throughput genomic measurements. It remains unclear though, how complex genome alterations affect molecular networks through changing protein levels, and consequently biochemical states of tumor tissues. ResultsHere, we investigated the propagation of genomic effects along the axis of gene expression during prostate cancer progression. For that, we quantified genomic, transcriptomic and proteomic alterations based on 105 prostate samples, consisting of benign prostatic hyperplasia regions and malignant tumors, from 39 prostate cancer patients. Our analysis revealed convergent effects of distinct copy number alterations impacting on common downstream proteins, which are important for establishing the tumor phenotype. We devised a network-based approach that integrates perturbations across different molecular layers, which identified a sub-network consisting of nine genes whose joint activity positively correlated with increasingly aggressive tumor phenotypes and was predictive of recurrence-free survival. Further, our data revealed a wide spectrum of intra-patient network effects, ranging from similar to very distinct alterations on different molecular layers. ConclusionsThis study uncovered molecular networks with remarkably convergent alterations across tumor sites and patients, but it also exposed a diversity of network effects: we could not identify a single sub-network that was perturbed in all high-grade tumor regions.

systems biology↗

A generalizable multivariate brain pattern for interpersonal guilt

Feeling guilty when we have wronged another is a crucial aspect of prosociality, but its neurobiological bases are elusive. Although multivariate patterns of brain activity show promise for developing brain measures linked to specific emotions, it is less clear whether brain activity can be trained to detect more complex social emotional states such as guilt. Here, we identified a distributed Guilt-Related Brain Signature (GRBS) across two independent neuroimaging datasets that used interpersonal interactions to evoke guilt. This signature discriminated conditions associated with interpersonal guilt from closely matched control conditions in a cross-validated training sample (N = 24; Chinese population) and in an independent test sample (N = 19; Swiss population). However, it did not respond to observed or experienced pain, or recalled guilt. Moreover, the GRBS only exhibited weak spatial similarity with other brain signatures of social affective processes, further indicating the specificity of the brain state it represents. These findings provide a step towards developing biological markers of social emotions, which could serve as important tools to investigate guilt-related brain processes in both healthy and clinical populations.

neuroscience↗

Multi-region proteome analysis quantifies spatial heterogeneity of prostate tissue biomarkers

Many tumors are characterized by large genomic heterogeneity and it remains unclear to what extent this impacts on protein biomarker discovery. Here, we quantified proteome intra-tissue heterogeneity (ITH) based on a multi-region analysis of 30 biopsy-scale prostate tissues using pressure cycling technology and SWATH mass spectrometry. We quantified 8,248 proteins and analyzed the ITH of 3,700 proteins. The level of ITH varied significantly depending on proteins and tissue types. Benign tissues exhibited generally more complex ITH patterns than malignant tissues. Spatial variability of ten prostate biomarkers was further validated by immunohistochemistry in an independent cohort (n=83) using tissue microarrays. PSA was preferentially variable in benign prostatic hyperplasia, while GDF15 substantially varied in prostate adenocarcinomas. Further, we found that DNA repair pathways exhibited a high degree of variability in tumorous tissues, which may contribute to the genetic heterogeneity of tumors. This study conceptually adds a new perspective to protein biomarker discovery by quantifying spatial proteome variation and it demonstrates the feasibility by exploiting recent technological progress.

systems biology↗