Evolving ribonucleocapsid assembly/packaging signals in the genomes of the human and animal coronaviruses: targeting, transmission and evolution

Molecular insight into the specific interactions of the SARS-Coronavirus-2 nucleocapsid with RNA and host protein

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) nucleocapsid protein is the most abundantly expressed viral protein during infection where it targets both RNA and host proteins. However, identifying how a single viral protein interacts with so many different targets remains a challenge, providing the impetus here for identifying the interaction sites through multiple methods. Through a combination of nuclear magnetic resonance (NMR), electron microscopy, and biochemical methods, we have characterized nucleocapsid interactions with RNA and with three host proteins, which include human cyclophilin-A, Pin1, and 14-3-3τ. Regarding RNA interactions, the nucleocapsid protein N-terminal folded domain preferentially interacts with smaller RNA fragments relative to the C-terminal region, suggesting an initial RNA engagement is largely dictated by this N-terminal region followed by weaker interactions to the C-terminal region. The nucleocapsid protein forms 10 nm ribonuclear complexes with larger RNA fragments that include 200 and 354 nucleic acids, revealing its potential diversity in sequestering different viral genomic regions during viral packaging. Regarding host protein interactions, while the nucleocapsid targets all three host proteins through its serine-arginine-rich region, unstructured termini of the nucleocapsid protein also engage host cyclophilin-A and host 14-3-3τ. Considering these host proteins play roles in innate immunity, the SARS-CoV-2 nucleocapsid protein may block the host response by competing interactions. Finally, phosphorylation of the nucleocapsid protein quenches an inherent dynamic exchange process within its serine-arginine-rich region. Our studies identify many of the diverse interactions that may be important for SARS-CoV-2 pathology during infection.

Genome-Wide Study of Colocalization between Genomic Stretches: A Method and Applications to the Regulation of Gene Expression

In this paper, we describe a method for the study of colocalization effects between stretch-stretch and stretch-point genome tracks based on a set of indices varying within the (-1, +1) interval. The indices combine the distances between the centers of neighboring stretches and their lengths. The extreme boundaries of the interval correspond to the complete colocalization of the genome tracks or its complete absence. We also obtained the relevant criteria of statistical significance for such indices using the complete permutation test. The method is robust with respect to strongly inhomogeneous positioning and length distribution of the genome tracks. On the basis of this approach, we created command-line software, the Genome Track Colocalization Analyzer. The software was tested, compared with other available packages, and applied to particular problems related to gene expression. The package, Genome Track Colocalization Analyzer (GTCA), is freely available to the users. GTCA complements our previous software, the Genome Track Analyzer, intended for the search for pairwise correlations between point-like genome tracks (also freely available). The corresponding details are provided in Data Availability Statement at the end of the text.