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Viruses must efficiently and specifically package their genomes while excluding cellular nucleic acids and viral sub-genomic fragments. Some viruses use specific packaging signals, which are conserved sequence/structure motifs present only in the full-length genome. Recent work has shown that viral proteins important for packaging can undergo liquid-liquid phase separation (LLPS), where one or two viral nucleic acid binding proteins condense with the genome. The compositional simplicity of viral components lends itself well to theoretical modeling compared to more complex cellular organelles. Viral LLPS can be limited to one or two viral proteins and a single genome that is enriched in LLPS-promoting features. In our previous study, we observed that LLPS-promoting sequences of SARS-CoV-2 are located at the 5' and 3' ends of the genome, whereas the middle of the genome is predicted to consist mostly of solubilizing elements. Is this arrangement sufficient to drive single genome packaging, genome compaction, and genome cyclization? We addressed these questions using a coarse-grained polymer model, LASSI, to study the LLPS of nucleocapsid protein with RNA sequences that either promote LLPS or solubilization. With respect to genome cyclization, we find the most optimal arrangement restricts LLPS-promoting elements to the 5' and 3' ends of the genome, consistent with the native spatial patterning. Genome compaction is enhanced by clustered LLPS-promoting binding sites, while single genome packaging is most efficient when binding sites are distributed throughout the genome. These results suggest that many and variably positioned LLPS-promoting signals can support packaging in the absence of a singular packaging signal which argues against necessity of such a feature. We hypothesize that this model should be generalizable to multiple viruses as well as cellular organelles like paraspeckles, which enrich specific, long RNA sequences in a defined arrangement.
Pubmed ID: 33442696
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A Python-based environment of open-source software for mathematics, science, and engineering. The core packages of SciPy include: NumPy, a base N-dimensional array package; SciPy Library, a fundamental library for scientific computing; and IPython, an enhanced interactive console.
View all literature mentionsPython 2D plotting library which produces publication quality figures in variety of hardcopy formats and interactive environments across platforms. Used in python scripts, web application servers, and six graphical user interface toolkits. Used to generate plots, histograms, power spectra, bar charts, error charts, scatter plots.
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