RanBP9 controls the oligomeric state of CTLH complex assemblies.

The CTLH (C-terminal to lissencephaly-1 homology motif) complex is a multisubunit RING E3 ligase with poorly defined substrate specificity and flexible subunit composition. Two key subunits, muskelin and Wdr26, specify two alternative CTLH complexes that differ in quaternary structure, thereby allowing the E3 ligase to presumably target different substrates. With the aid of different biophysical and biochemical techniques, we characterized CTLH complex assembly pathways, focusing not only on Wdr26 and muskelin but also on RanBP9, Twa1, and Armc8ß subunits, which are critical to establish the scaffold of this E3 ligase. We demonstrate that the ability of muskelin to tetramerize and the assembly of Wdr26 into dimers define mutually exclusive oligomerization modules that compete with nanomolar affinity for RanBP9 binding. The remaining scaffolding subunits, Armc8ß and Twa1, strongly interact with each other and with RanBP9, again with nanomolar affinity. Our data demonstrate that RanBP9 organizes subunit assembly and prevents higher order oligomerization of dimeric Wdr26 and the Armc8ß-Twa1 heterodimer through its tight binding. Combined, our studies define alternative assembly pathways of the CTLH complex and elucidate the role of RanBP9 in governing differential oligomeric assemblies, thereby advancing our mechanistic understanding of CTLH complex architectures.

Prediction and validation of host-pathogen interactions by a versatile inference approach using Aspergillus fumigatus as a case study.

Biological networks are characterized by diverse interactions and dynamics in time and space. Many regulatory modules operate in parallel and are interconnected with each other. Some pathways are functionally known and annotated accordingly, e.g., endocytosis, migration, or cytoskeletal rearrangement. However, many interactions are not so well characterized. For reconstructing the biological complexity in cellular networks, we combine here existing experimentally confirmed and analyzed interactions with a protein-interaction inference framework using as basis experimentally confirmed interactions from other organisms. Prediction scoring includes sequence similarity, evolutionary conservation of interactions, the coexistence of interactions in the same pathway, orthology as well as structure similarity to rank and compare inferred interactions. We exemplify our inference method by studying host-pathogen interactions during infection of Mus musculus (phagolysosomes in alveolar macrophages) with Aspergillus fumigatus (conidia, airborne, asexual spores). Three of nine predicted critical host-pathogen interactions could even be confirmed by direct experiments. Moreover, we suggest drugs that manipulate the host-pathogen interaction.