Poster #69 - Vaughn Flippen

Identifying Adaptive Mutations in Rubella Virus Using the c/μ Method

Vaughn Flippen, B.S. Candidate, Biological Sciences, Rowan University; Chun Wu, Ph.D., Department of Chemistry and Biochemistry & Department of Biological and Biomedical Sciences, Glassboro, NJ 08028, USA

Rubella Virus (RV) is a positive-sense RNA virus (+ssRNA) belonging to the Matonaviridae family. It typically causes mild fever and rashes in children and adults but poses a severe risk to pregnant women, where infection can cause Congenital Rubella Syndrome (CRS) leading to serious birth defects. RV has persisted in populations despite widespread vaccination. Investigating RV mutations could give insight into viral adaptation and immune escape. In this study, we applied substitution to mutation rate ratio (c/μ) method previously validated in SARS-Cov2 to RV genomic sequence data to identify adaptive mutations and molecular evolution. c/μ quantifies observed substitution (c) and neutral mutation rate (μ), independent of other factors such as genome location or time. Using this approach we have identified the top adaptive nonsynonymous mutations across the Rubella genome in both Translated Regions (TR) and Untranslated Regions (UTR). Mutations were concentrated in Non-structural polyprotein (NSP) and Structural Proteins (SP). Mutations overlapped with literature findings, providing support of c/μ predictions. Several of the top mutations were found in the E1/ E2 glycoproteins, which are important to viral entry and assembly as well as in the p150/p90 NSP that form the replication complex. These proteins are already considered key drug and vaccine targets, the adaptive mutations present in these regions with potential implications for drug and vaccine design, highlights candidates for future investigation. The RV genome displayed an L-shaped distribution of fitness, which is consistent with Near Neutral Selectionist Theory (NNST). This suggests that near neutral mutations drive the formation/absence of the molecular clock. These findings support the value of c/μ as a predictive framework examining viral evolution for RV, and providing a set of mutation candidates for future modeling and the development of next-generation vaccines and drug therapeutics.