Arnold, C. — Page 2 | bioRxiv Science

bioRxiv2019

XIAP controls RIPK2 signaling by preventing its deposition in speck-like structures

The receptor interacting serine/threonine kinase 2 (RIPK2) is essential for linking activation of the pattern recognition receptors NOD1 and NOD2 to cellular signaling events. Recently, it was shown that RIPK2 forms higher order molecular structures in vitro, which were proposed to activate signaling. Here, we demonstrate that RIPK2 forms detergent insoluble complexes in the cytosol of host cells upon infection with invasive enteropathogenic bacteria. Formation of these structures occurred after NF-{kappa}B activation and depends on the CARD of NOD1 or NOD2. Complex formation upon activation was dependent on RIPK2 autophosphorylation at Y474 and influenced by phosphorylation at S176. Inhibition of activity of the cIAP protein XIAP induced spontaneous complex formation of RIPK2 but blocked NOD1-dependet NF-{kappa}B activation. Using immunoprecipitation, we identified 14-3-3 proteins as novel binding partners of non-activated RIPK2, whereas complexed RIPK2 was bound by the prohibitin proteins Erlin-1 and Erlin-2. Taken together, our work reveals novel roles of XIAP, 14-3-3 and Erlin proteins in the regulation of RIPK2 and expands our knowledge on the function of RIPK2 posttranslational modifications in NOD1/2 signaling.

immunology↗

bioRxiv2018

Quantification of differential transcription factor activity and multiomic-based classification into activators and repressors: diffTF

Transcription factor (TF) activity is an important read-out of cellular signalling pathways and thus to assess regulatory differences across conditions. However, current technologies lack the ability to simultaneously assess activity changes for multiple TFs and in particular to determine whether a specific TF acts globally as transcriptional repressor or activator. To this end, we introduce a widely applicable genome-wide method diffTF to assess differential TF activity and to classify TFs as activator or repressor (available at https://git.embl.de/grp-zaugg/diffTF). This is done by integrating any type of genome-wide chromatin accessibility data with RNA-Seq data and in-silico predicted TF binding sites. We corroborated the classification of TFs into repressors and activators by three independent analyses based on enrichments of active/repressive chromatin states, correlation of TF activity with gene expression, and activator-and repressor-specific chromatin footprints. To show the power of diffTF, we present two case studies: First, we applied diffTF in to a large ATAC-Seq/RNA-Seq dataset comparing mutated and unmutated chronic lymphocytic leukemia samples, where we identified dozens of known (40%) and potentially novel (60%) TFs that are differentially active. We were also able to classify almost half of them as either repressor and activator. Second, we applied diffTF to a small ATAC-Seq/RNA-Seq data set comparing two cell types along the hematopoietic differentiation trajectory (multipotent progenitors - MPP - versus granulocyte-macrophage progenitors - GMP). Here we identified the known drivers of differentiation and found that the majority of the differentially active TFs are transcriptional activators. Overall, diffTF was able to recover the known TFs in both case studies, additionally identified TFs that have been less well characterized in the given condition, and provides a classification of the TFs into transcriptional activators and repressors.

bioinformatics↗

bioRxiv2017

Alzheimer related genes show accelerated evolution

Alzheimer's disease (AD) is a neurodegenerative disorder of unknown cause with complex genetic and environmental traits. Here, we show that gene structures of loci, that show AD-associated changes in their expression, evolve faster than the genome at large. This phylogenetic trait of AD suggests a critical pathogenetic role of recent adaptive evolution of human brain and might have far reaching consequences with respect to the appropriateness of model systems and the development of disease-modifying strategies.

evolutionary biology↗