Author Correction: Determination of RNA structural diversity and its role in HIV-1 RNA splicing.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Determination of RNA structural diversity and its role in HIV-1 RNA splicing.

Human immunodeficiency virus 1 (HIV-1) is a retrovirus with a ten-kilobase single-stranded RNA genome. HIV-1 must express all of its gene products from a single primary transcript, which undergoes alternative splicing to produce diverse protein products that include structural proteins and regulatory factors1,2. Despite the critical role of alternative splicing, the mechanisms that drive the choice of splice site are poorly understood. Synonymous RNA mutations that lead to severe defects in splicing and viral replication indicate the presence of unknown cis-regulatory elements3. Here we use dimethyl sulfate mutational profiling with sequencing (DMS-MaPseq) to investigate the structure of HIV-1 RNA in cells, and develop an algorithm that we name 'detection of RNA folding ensembles using expectation-maximization' (DREEM), which reveals the alternative conformations that are assumed by the same RNA sequence. Contrary to previous models that have analysed population averages4, our results reveal heterogeneous regions of RNA structure across the entire HIV-1 genome. In addition to confirming that in vitro characterized5 alternative structures for the HIV-1 Rev responsive element also exist in cells, we discover alternative conformations at critical splice sites that influence the ratio of transcript isoforms. Our simultaneous measurement of splicing and intracellular RNA structure provides evidence for the long-standing hypothesis6-8 that heterogeneity in RNA conformation regulates splice-site use and viral gene expression.

Human cytokine and coronavirus nucleocapsid protein interactivity using large-scale virtual screens.

Understanding the interactions between SARS-CoV-2 and the human immune system is paramount to the characterization of novel variants as the virus co-evolves with the human host. In this study, we employed state-of-the-art molecular docking tools to conduct large-scale virtual screens, predicting the binding affinities between 64 human cytokines against 17 nucleocapsid proteins from six betacoronaviruses. Our comprehensive in silico analyses reveal specific changes in cytokine-nucleocapsid protein interactions, shedding light on potential modulators of the host immune response during infection. These findings offer valuable insights into the molecular mechanisms underlying viral pathogenesis and may guide the future development of targeted interventions. This manuscript serves as insight into the comparison of deep learning based AlphaFold2-Multimer and the semi-physicochemical based HADDOCK for protein-protein docking. We show the two methods are complementary in their predictive capabilities. We also introduce a novel algorithm for rapidly assessing the binding interface of protein-protein docks using graph edit distance: graph-based interface residue assessment function (GIRAF). The high-performance computational framework presented here will not only aid in accelerating the discovery of effective interventions against emerging viral threats, but extend to other applications of high throughput protein-protein screens.

Lessons Learned From Limited Overlap of 15 In Vitro COVID-19 Drug Repurposing Screens.

Drug repurposing can quickly and cost-effectively identify medical countermeasures against pathogens with pandemic potential and could be used as a down-selection method for selecting US Food and Drug Administration-approved drugs to test in clinical trials. We compared results from 15 high-throughput in vitro screening efforts that tested approved and clinically evaluated drugs for activity against SARS-CoV-2 replication. From the 15 studies, 304 drugs were identified as displaying the highest level of confidence from the individual screens. Of those 304 drugs, 30 were identified in 2 or more screens, while only 3 drugs (apilimod, tetrandrine, and salinomycin) were identified in 4 screens. The lack of concordance in high-confidence hits and variations in protocols makes it challenging to use the collective data as down-selection criteria for identifying repurposing candidates to move into a clinical trial.

Antigen-specific memory NK cell responses against HIV and influenza use the NKG2/HLA-E axis.

Multiple studies have broadened the roles of natural killer (NK) cells functioning as purely innate lymphocytes by demonstrating that they are capable of putative antigen-specific immunological memory against multiple infectious agents including HIV-1 and influenza. However, the mechanisms underlying antigen specificity remain unknown. Here, we demonstrate that antigen-specific human NK cell memory develops upon exposure to both HIV and influenza, unified by a conserved and epitope-specific targetable mechanism largely dependent on the activating CD94/NKG2C receptor and its ligand HLA-E. We validated the permanent acquisition of antigen specificity by individual memory NK cells by single-cell cloning. We identified elevated expression of KLRG1, α4ß7, and NKG2C as biomarkers of antigen-specific NK cell memory through complex immunophenotyping. Last, we uncovered individual HLA-E-restricted peptides that may constitute the dominant NK cell response in HIV-1- and influenza-infected persons in vivo. Our findings clarify the mechanisms contributing to antigen-specific memory NK cell responses and suggest that they could be potentially targeted therapeutically for vaccines or other therapeutic interventions.