No abstract

Human respiratory syncytial virus (RSV) nonstructural protein 2 (NS2) inhibits host interferon (IFN) responses stimulated by RSV infection by targeting early steps in the IFN-signaling pathway. But the molecular mechanisms related to how NS2 regulates these processes remain incompletely understood. To address this gap, here we solved the X-ray crystal structure of NS2. This structure revealed a unique fold that is distinct from other known viral IFN antagonists, including RSV NS1. We also show that NS2 directly interacts with an inactive conformation of the RIG-I–like receptors (RLRs) RIG-I and MDA5. NS2 binding prevents RLR ubiquitination, a process critical for prolonged activation of downstream signaling. Structural analysis, including by hydrogen-deuterium exchange coupled to mass spectrometry, revealed that the N terminus of NS2 is essential for binding to the RIG-I caspase activation and recruitment domains. N-terminal mutations significantly diminish RIG-I interactions and result in increased IFNβ messenger RNA levels. Collectively, our studies uncover a previously unappreciated regulatory mechanism by which NS2 further modulates host responses and define an approach for targeting host responses.

Here, an analysis is performed of how uncorrected antisymmetric aberrations, such as coma and trefoil, affect cryo-EM single-particle reconstruction (SPR) results, and an analytical formula quantifying information loss owing to their presence is inferred that explains why Fourier-shell coefficient-based statistics may report significantly overestimated resolution if these aberrations are not fully corrected. The analysis is validated with reference-based aberration refinement for two cryo-EM SPR data sets acquired with a 200 kV microscope in the presence of coma exceeding 40 µm, and 2.3 and 2.7 Å reconstructions for 144 and 173 kDa particles, respectively, were obtained. The results provide a description of an efficient approach for assessing information loss in cryo-EM SPR data acquired in the presence of higher order aberrations, and address inconsistent guidelines regarding the level of aberrations that is acceptable in cryo-EM SPR experiments.

The human genome harbors a variety of genetic variations. Single-nucleotide changes that alter amino acids in protein-coding regions are one of the major causes of human phenotypic variation and diseases. These single-amino acid variations (SAVs) are routinely found in whole genome and exome sequencing. Evaluating the functional impact of such genomic alterations is crucial for diagnosis of genetic disorders. We developed DeepSAV, a deeplearning convolutional neural network to differentiate disease-causing and benign SAVs based on a variety of protein sequence, structural and functional properties. Our method outperforms most stand-alone programs, and the version incorporating population and gene-level information (DeepSAV+PG) has similar predictive power as some of the best available. We transformed DeepSAV scores of rare SAVs in the human population into a quantity termed "mutation severity measure" for each human protein-coding gene. It reflects a gene's tolerance to deleterious missense mutations and serves as a useful tool to study gene-disease associations. Genes implicated in cancer, autism, and viral interaction are found by this measure as intolerant to mutations, while genes associated with a number of other diseases are scored as tolerant. Among known disease-associated genes, those that are mutation-intolerant are likely to function in development and signal transduction pathways, while those that are mutation-tolerant tend to encode metabolic and mitochondrial proteins.

Chromatin structure undergoes many changes during the cell cycle and in response to regulatory events. A basic unit of chromatin organization is the nucleosome core particle. However, very little is known about how nucleosomes are arranged into higher-order structures in vivo, even though the efficiency and precision of cell division imply high levels of structural organization. We propose abandoning the current paradigm of chromatin organization based on thermodynamics of the lowest energy state and replace it with the idea of a topologically restrained, high-energy structure. We propose that DNA is subject to a recursive topological restraint, and is anchored by hemicatenates that are part of the chromosomal scaffold. Long-distance cis-regulation of transcription is a natural consequence of recursive topological restraint. This new theory of