The spatial organization of RNA-scaffolded condensates is fundamental for understanding of basic cellular functions, but may also provide pivotal insights into diseases. One of the major challenges to understanding the role of condensates is the lack of technologies to map condensate-scale protein architecture at subcompartmental resolution. To address this, we introduce HCR-Proxy, a proximity labelling technique that couples hybridization chain reaction (HCR)-based signal amplification with in situ proximity biotinylation (Proxy), enabling proteomic profiling of RNA-proximal proteomes at subcompartmental resolution. We applied HCR-Proxy to nascent pre-rRNA targets to investigate the distinct proteomic signatures of the nucleolar subcompartments and to uncover a spatial logic of protein partitioning shaped by RNA sequence. Our results demonstrate the ability of HCR-Proxy to provide spatially resolved maps of RNA interactomes within the nucleolus, offering new insights into the molecular organization and compartmentalization of condensates. This subcompartment-specific nucleolar proteome profiling enabled integration with deep learning frameworks, which effectively confirmed a sequence-encoded basis for protein partitioning across nested condensate subcompartments, characterized by antagonistic gradients in charge, molecular weight, and RNA-binding domains. HCR-Proxy thus provides a scalable platform for spatially resolved RNA interactome discovery, bridging transcript localization with proteomic context in native cellular environments.
Trupej et al. (Thu,) studied this question.