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Weishaupt, J.

Publications and source records attributed to Weishaupt, J..

2 recordsLinked to original sources

Herpes simplex virus infection promotes ALS pathology through ICP0-mediated PML body disruption

Transactive response DNA binding protein 43 kDa (TDP-43) pathology, is a central molecular hallmark of amyotrophic lateral sclerosis (ALS). However, the underlying triggers are incompletely understood. Here, we show that infection with herpes simplex virus (HSV) induces molecular hallmarks of ALS in various in vitro and in vivo models and is associated with an increased risk of ALS in human population data. German healthcare provider data (n = 238,440) and herpesvirus serology of an ALS patient and control cohort (n = 1,100) showed that HSV infection elevated the ALS risk by 210% and odds by [~]65%, respectively. On a molecular level, HSV infection promoted TDP-43 pathology in neuronal cell models, human iPSC-derived motoneurons and cerebral organoids, mice, and human tissue sections. This effect was triggered by HSV-1 or 2, but not by several other related herpesviruses. Mechanistically, the infected cell protein 0 (ICP0) of HSV-1/2 drives TDP-43 pathology by disturbance of promyelocytic leukemia nuclear bodies (PML-NBs), thereby abrogating TDP-43 SUMO2/3ylation. Taken together, we reveal a previously unrecognized association between HSV infection and ALS and clarify the underlying molecular mechanism that drives TDP-43 pathology. Our data may guide future studies into therapeutic and prophylactic interventions against ALS.

neuroscience↗

Identifying similar populations across independent single cell studies without data integration

Supervised and unsupervised methods have emerged to address the complexity of single cell data analysis in the context of large pools of independent studies. Here, we present ClusterFoldSimilarity (CFS), a novel statistical method design to quantify the similarity between cell groups acroos any number of independent datasets, without the need for data correction or integration. By bypassing these processes, CFS avoids the introduction of artifacts and loss of information, offering a simple, efficient, and scalable solution. This method match groups of cells that exhibit conserved phenotypes across datasets, including different tissues and species, and in a multimodal scenario, including single-cell RNA-Seq, ATAC-Seq, single-cell proteomics, or, more broadly, data exhibiting differential abundance effects among groups of cells. Additionally, CFS performs feature selection, obtaining cross-dataset markers of the similar phenotypes observed, providing an inherent interpretability of relationships between cell populations. To showcase the effectiveness of our methodology we generated single-nuclei RNA-Seq data from the motor cortex and spinal cord of adult mice. By using CFS, we identified three distinct sub-populations of astrocytes conserved on both tissues. CFS includes various visualization methods for the interpretation of the similarity scores and similar cell populations.

bioinformatics↗