Upper airway epithelial tissue transcriptome analysis reveals immune signatures associated with COVID-19 severity in Ghanaians.

The immunological signatures driving the severity of coronavirus disease 19 (COVID-19) in Ghanaians remain poorly understood. We performed bulk transcriptome sequencing of nasopharyngeal samples from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-infected Ghanaians with mild and severe COVID-19, as well as healthy controls to characterize immune signatures at the primary SARS-CoV-2 infection site and identify drivers of disease severity. Generally, a heightened antiviral response was observed in SARS-CoV-2-infected Ghanaians compared with uninfected controls. COVID-19 severity was associated with immune suppression, overexpression of proinflammatory cytokines, including CRNN, IL1A, S100A7, and IL23A, and activation of pathways involved in keratinocyte proliferation. SAMD9L was among the differentially regulated interferon-stimulated genes in our mild and severe disease cohorts, suggesting that it may play a critical role in SARS-CoV-2 pathogenesis. By comparing our data with a publicly available dataset from a non-African (Indians) (GSE166530), an elevated expression of antiviral response-related genes was noted in COVID-19-infected Ghanaians. Overall, the study describes immune signatures driving COVID-19 severity in Ghanaians and identifies immune drivers that could serve as potential prognostic markers for future outbreaks or pandemics. It further provides important preliminary evidence suggesting differences in antiviral response at the upper respiratory interface in sub-Saharan Africans (Ghanaians) and non-Africans, which could be contributing to the differences in disease outcomes. Further studies using larger datasets from different populations will expand on these findings

Additional file 4 of Probing SARS-CoV-2-positive plasma to identify potential factors correlating with mild COVID-19 in Ghana, West Africa

Additional file 4. Cytokine concentration levels in COVID-19 patients. Comparison of cytokine concentration levels between COVID-19 symptomatic, asymptomatic patients, pre-COVID-19 health participants, COVID-19 pandemic health individuals and COVID-19 non-survivors. The cytokine concentration levels were measured from plasma of COVID-19 symptomatic (n = 29) and asymptomatic (n = 29), individuals, pre-COVID-19 health participants (100), COVID-19 pandemic health individuals (33) and COVID-19 non-survivors (2). The median quantity of the cytokines is shown by a horizontal line across the scatter plot while the lower and upper dotted lines represent the 25th and 75th percentiles, respectively. Statistical significance between symptomatic and asymptomatic patients were determined by a Kruskal-Wallis test with Dunn’s post hoc. (*: p 0.05)

Additional file 3 of Probing SARS-CoV-2-positive plasma to identify potential factors correlating with mild COVID-19 in Ghana, West Africa

Additional file 3. Antibody profiles among SARS-CoV-2 infected patients. A: The kinetics of IgG in asymptomatic individuals (n = 3) in response to SARS-CoV-2. Data represents the quantity of the multiple time points of the cytokines, B: Differential expression levels of IgG against SARS-CoV-2 spike and nucleocapsid proteins in symptomatic in response to COVID-19. Data represents the median quantity with the 25th and 75th percentiles

Additional file 6 of Probing SARS-CoV-2-positive plasma to identify potential factors correlating with mild COVID-19 in Ghana, West Africa

Additional file 6. Coronavirus disease 2019’s fatality rate in the world and Africa. The data was retrieved from WHO COVID-19 dashboard ( https://covid19.who.int/ ). The COVID-19 vaccine was rolled out in December 2020 worldwide and in February/March 2021 in Africa

Additional file 8 of Probing SARS-CoV-2-positive plasma to identify potential factors correlating with mild COVID-19 in Ghana, West Africa

Additional file 8: Table S1. The median cytokine levels of healthy individuals (n = 124). Table S2. Heathy control samples used in the study

Additional file 2 of Probing SARS-CoV-2-positive plasma to identify potential factors correlating with mild COVID-19 in Ghana, West Africa

Additional file 2. Change on cytokine concentration levels over time in COVID-19 positive individuals. The cytokine concentration levels analysed from plasma of COVID-19 asymptomatic (n = 3), monthly for four months. The quantity of the cytokines for each sampling month is shown by the line graph

Additional file 5 of Probing SARS-CoV-2-positive plasma to identify potential factors correlating with mild COVID-19 in Ghana, West Africa

Additional file 5. The half-life of cytokines in asymptomatic and symptomatic patients. The cytokine concentration levels were for cytokines with significant difference between symptomatic and asymptomatic cases (14 cytokines), pro-inflammatory, anti-inflammatory and chemokines. The median half-life of the cytokines is shown by a horizontal line across the dot plot while the lower and upper dotted lines represent the 25th and 75th percentiles, respectively. Statistical significance between symptomatic and asymptomatic patients were determined by Mann-Whitney test (*: p 0.05)

Additional file 7 of Probing SARS-CoV-2-positive plasma to identify potential factors correlating with mild COVID-19 in Ghana, West Africa

Additional file 7. The Pearson correlation coefficient (r) between concentration levels of cytokines with significant difference between symptomatic and asymptomatic cases (14 cytokines), and baseline viral loads (Ct value) of the patients at p value<0.05

Seizures Are Regulated by Ubiquitin-specific Peptidase 9 X-linked (USP9X), a De-Ubiquitinase

<div><p>Epilepsy is a common disabling disease with complex, multifactorial genetic and environmental etiology. The small fraction of epilepsies subject to Mendelian inheritance offers key insight into epilepsy disease mechanisms; and pathologies brought on by mutations in a single gene can point the way to generalizable therapeutic strategies. Mutations in the PRICKLE genes can cause seizures in humans, zebrafish, mice, and flies, suggesting the seizure-suppression pathway is evolutionarily conserved. This pathway has never been targeted for novel anti-seizure treatments. Here, the mammalian PRICKLE-interactome was defined, identifying prickle-interacting proteins that localize to synapses and a novel interacting partner, USP9X, a substrate-specific de-ubiquitinase. PRICKLE and USP9X interact through their carboxy-termini; and USP9X de-ubiquitinates PRICKLE, protecting it from proteasomal degradation. In forebrain neurons of mice, USP9X deficiency reduced levels of Prickle2 protein. Genetic analysis suggests the same pathway regulates Prickle-mediated seizures. The seizure phenotype was suppressed in <i>prickle</i> mutant flies by the small-molecule USP9X inhibitor, Degrasyn/WP1130, or by reducing the dose of <i>fat facets</i> a <i>USP9X</i> orthologue. <i>USP9X</i> mutations were identified by resequencing a cohort of patients with epileptic encephalopathy, one patient harbored a <i>de novo</i> missense mutation and another a novel coding mutation. Both <i>USP9X</i> variants were outside the PRICKLE-interacting domain. These findings demonstrate that USP9X inhibition can suppress <i>prickle</i>-mediated seizure activity, and that <i>USP9X</i> variants may predispose to seizures. These studies point to a new target for anti-seizure therapy and illustrate the translational power of studying diseases in species across the evolutionary spectrum.</p></div

Prickle interactome.

<p>We combined findings from our proteomics interaction experiment and public databases to generate a prickle interactome. We used the MetaCore (MetaCore, GeneGO Inc., St. Joseph, MI, USA) networking function and String database 9.1 to curate interaction maps of the proteins identified. Information for identified interactions is obtained from several sources including but not limited to genomic context, database imports (PPI and pathway databases), high-throughput experiments, co-expression, and text mining. We uploaded our lists of proteins from LC-MS/MS into the software programs and exported the networks into Cytoscape 2.7.0 for manipulation of the network appearance. (Nodes, circles; Edges, lines). Red lines correspond to interactions observed by our labs using yeast-2-hybrid and IP-MS approaches. The extended interactome was generated as we have previously described. [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005022#pgen.1005022.ref001" target="_blank">1</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005022#pgen.1005022.ref006" target="_blank">6</a>–<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005022#pgen.1005022.ref009" target="_blank">9</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005022#pgen.1005022.ref018" target="_blank">18</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005022#pgen.1005022.ref019" target="_blank">19</a>] Prickle1 and Prickle2 interact with known synaptic proteins. The interaction with USP9X is novel.</p