04/11/21
Researchers from the Centre for Developmental Neurobiology have published a new paper, out now in Molecular Cell, which offers a suite of tools for dissecting RNA interactomes for biomedical research and provides new insights into the functional architecture of the nucleus.
Compartmentalisation improves the efficiency of a myriad of subcellular processes as it concentrates the necessary components to a confined space and allows optimal efficiency and the precise regulation of biological processes. The structure and function of many of these compartments depend upon RNA molecules. Some RNA-containing compartments may form specific contacts with various genomic regions, suggesting a role in higher-order nuclear organisation.
Given that mammalian cells produce numerous long noncoding transcripts with yet to be understood functions, RNA-dependent compartmentalisation may be more prevalent and important than currently thought. One currently used approach to analyse subcellular compartments involves expression of recombinant proximity labelling enzymes in living cells. This is a powerful technology, but its scope is limited to genetically tractable systems. Furthermore, the design and expression levels of the fusion proteins used in published protocols must be carefully optimised, which can be time-consuming and costly.
In their new work, Karen Yap, Tek Hong Chung, and Eugene Makeyev describe a straightforward approach to analysing RNA-protein and RNA-RNA proximity patterns in genetically unmodified cells. Briefly, fixed and permeabilised cells are hybridised with digoxigenin-labelled probes against the RNA of interest followed by the recruitment of a recombinant hybridization-proximity labelling (HyPro) enzyme and unbiased discovery of RNA-proximal proteins (HyPro-MS) and transcripts (HyPro-seq). Yap et al. used HyPro-MS and HyPro-seq to profile spatial interactomes of RNA-containing nuclear bodies, showing that the new approach can uncover new interactions, cellular structures and gene regulation mechanisms.
Senior author, Professor Eugene Makeyev, commented:
“We hope that our technology will help researchers investigating RNA functions in health and disease to advance their studies and translate them into practical applications”
