Protein Condensate Atlas from predictive models of heteromolecular condensate composition.

Biomolecular condensates help cells organise their content in space and time. Cells harbour a variety of condensate types with diverse composition and many are likely yet to be discovered. Here, we develop a methodology to predict the composition of biomolecular condensates. We first analyse available proteomics data of cellular condensates and find that the biophysical features that determine protein localisation into condensates differ from known drivers of homotypic phase separation processes, with charge mediated protein-RNA and hydrophobicity mediated protein-protein interactions playing a key role in the former process. We then develop a machine learning model that links protein sequence to its propensity to localise into heteromolecular condensates. We apply the model across the proteome and find many of the top-ranked targets outside the original training data to localise into condensates as confirmed by orthogonal immunohistochemical staining imaging. Finally, we segment the condensation-prone proteome into condensate types based on an overlap with biomolecular interaction profiles to generate a Protein Condensate Atlas. Several condensate clusters within the Atlas closely match the composition of experimentally characterised condensates or regions within them, suggesting that the Atlas can be valuable for identifying additional components within known condensate systems and discovering previously uncharacterised condensates.

Targeting the Conserved Stem Loop 2 Motif in the SARS-CoV-2 Genome.

RNA structural elements occur in numerous single-stranded positive-sense RNA viruses. The stem-loop 2 motif (s2m) is one such element with an unusually high degree of sequence conservation, being found in the 3' untranslated region (UTR) in the genomes of many astroviruses, some picornaviruses and noroviruses, and a variety of coronaviruses, including severe acute respiratory syndrome coronavirus (SARS-CoV) and SARS-CoV-2. The evolutionary conservation and its occurrence in all viral subgenomic transcripts imply a key role for s2m in the viral infection cycle. Our findings indicate that the element, while stably folded, can nonetheless be invaded and remodeled spontaneously by antisense oligonucleotides (ASOs) that initiate pairing in exposed loops and trigger efficient sequence-specific RNA cleavage in reporter assays. ASOs also act to inhibit replication in an astrovirus replicon model system in a sequence-specific, dose-dependent manner and inhibit SARS-CoV-2 replication in cell culture. Our results thus permit us to suggest that the s2m element is readily targeted by ASOs, which show promise as antiviral agents. IMPORTANCE The highly conserved stem-loop 2 motif (s2m) is found in the genomes of many RNA viruses, including SARS-CoV-2. Our findings indicate that the s2m element can be targeted by antisense oligonucleotides. The antiviral potential of this element represents a promising start for further research into targeting conserved elements in RNA viruses.