Holistic integration of protein interaction datasets establishes a framework for exploring the organization and composition of Caenorhabditis elegans germ granules

Abstract

Spatiotemporal organization of biological molecules is a key driver of cellular processes, including many post-transcriptional epigenetic processes. The germline-specific germ granules are biomolecular condensates that act as hubs for mRNA and small RNA processing and are core regulators of germline gene expression programming. Germ granules have been studied extensively in Caenorhabditis elegans, and recent developments have led to many subdivisions of the germ granule into specialized compartments. Rapid advancements in microscopy and protein-protein interaction (PPI) screening techniques have produced a large amount of data towards characterizing the localization of proteins to specific granules. However, common methods used to probe PPIs are limited in their ability to robustly detect valid interactions, especially the multivalent and sometimes transient ones observed in granule environments. Here we perform a meta-analysis of granule protein interaction screens. While these experiments generally enrich for proteins matching the profile of granule-associated proteins, we find that when considering screens individually, reproducibility is surprisingly low, highlighting not only the variability inherent in these methods but also the dynamic nature of the PPI networks present in granules. We developed an algorithm to provide a measure of each protein’s association with specific granules across various experiments (a “granule association metric” or GAM). By further clustering and investigation of the GAM matrix, we demonstrate the power of this holistic approach to provide deeper insights into germ granule organization, highlight novel candidates, and act as a resource to inform future investigations into granules and their constituent proteins.