Novel, Conserved RNA Secondary Structures in MHV-A59, Bovine Coronavirus (BCoV) and MERS-CoV

Betacoronaviruses are a subgroup of viruses in the family Coronaviradae known to cause an array of diseases in humans and animals. In this study, we aim to determine the RNA secondary structures of Mouse Hepatitis Virus, strain A59 (MHV-A59), the best studied betacoronavirus, and closely related betacoronaviruses, BCoV and MERS-CoV to identify novel, conserved secondary structures within their genomes. To accomplish this, we infected DBT, HRT, and Vero-E6 cell cultures with their respective virus stocks: MHV-A59, BCoV, and MERS-CoV. Upon viral clarification and titration, we obtained virus titers between 1.0 and 1.42x10^7 pfu/mL and purified viruses via differential and sucrose density gradient centrifugation. Subsequently, we extracted the viral RNA and reacted it with SHAPE-MaP reagent 1-methyl-7-nitroisatoic anhydride (IM7) which probes for and forms adducts with conformationally flexible ribose 2’-hydroxyl groups in the RNA. The derivatized RNA is reverse transcribed in the presence of Mn++ causing misincorporation at adduct sites. This induces mutations in the cDNA transcripts which are incorporated into a cDNA library. Thus, deep sequencing of this cDNA library provided us with an avenue to create relatively accurate RNA secondary structure models using Shannon entropy and pairing probability models. High-confidence regions, characterized by low Shannon entropy and low SHAPE reactivity, were selectivity visualized. The folding models generated by FORNA were visually analyzed for conserved structures and covariation. Three conserved secondary structure models, located in open reading frame (ORF) 1b, were isolated and are thought to be important in translation and could serve as binding sites for host or viral proteins. Further studies will include conducting site-directed mutagenesis to understand the functional role of these secondary structure models and utilizing ShapeKnots analysis to probe for psuedoknots

Validated Clinical Score to Predict Gastroesophageal Reflux in Patients With Chronic Laryngeal Symptoms: COuGH RefluX

Background & aimsDiscerning whether laryngeal symptoms result from gastroesophageal reflux is clinically challenging and a reliable tool to stratify patients is needed. We aimed to develop and validate a model to predict the likelihood of gastroesophageal reflux disease (GERD) among patients with chronic laryngeal symptoms.MethodsThis multicenter international study collected data from adults with chronic laryngeal symptoms who underwent objective testing (upper gastrointestinal endoscopy and/or ambulatory reflux monitoring) between March 2018 and May 2023. The training phase identified a model with optimal receiver operating characteristic curves, and β coefficients informed a weighted model. The validation phase assessed performance characteristics of the weighted model.ResultsA total of 856 adults, 304 in the training cohort and 552 in the validation cohort, were included. In the training phase, the optimal predictive model (area under the curve, 0.68; 95% CI, 0.62-0.74), was the Cough, Overweight/obesity, Globus, Hiatal Hernia, Regurgitation, and male seX (COuGH RefluX) score, with a lower threshold of 2.5 and an upper threshold of 5.0 to predict proven GERD. In the validation phase, the COuGH RefluX score had an area under the curve of 0.67 (95% CI, 0.62-0.71), with 79% sensitivity and 81% specificity for proven GERD.ConclusionsThe externally validated COuGH RefluX score is a clinically practical model to predict the likelihood of proven GERD. The score classifies most patients with chronic laryngeal symptoms as low/high likelihood of proven GERD, with only 38% remaining as indeterminate. Thus, the COuGH RefluX score can guide diagnostic strategies and reduce inappropriate proton pump inhibitor use or testing for patients referred for evaluation of chronic laryngeal symptoms