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Navigating Zika Virus Evolution with the Unprecedented Near-Neutral Balanced Selection Theory: Illum

Philip Gance, BS, Chemistry and Biological Science (gancep65@students.rowan.edu), Department of Molecular & Cellular Biosciences, College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028, United States. Nicholas Paradis, Ph.D., Pharmaceutical Science (paradi84@rowan.edu), Department of Molecular & Cellular Biosciences, College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028, United States. Chun Wu, Associate Professor (wuc@rowan.edu), Department of Molecular & Cellular Biosciences, College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028, United States.


Poster # 62


Zika virus (ZIKV), a positive-sense, single-stranded RNA virus, has two primary lineages within the Flaviviridae family and the Flavivirus genus. Its 10,794 nucleotides encode 3,421 amino acids for the seven virus protein sequences, three structural and four nonstructural. WHO's Public Health Emergency of International Concern (PHEIC) classification accelerated vaccine development against the virus, aiming to minimize neonatal neurological and congenital risk, yet unpredictable viral dynamics challenge formulating an effective vaccine against all viral strains. Focusing on the molecular evolution of the virus's envelope and membrane proteins can enhance vaccine design. ZIKV is currently suggested to follow Ohta's Nearly-Neutral Theory (ONNT) of molecular evolution due to the impact of high mutation rates caused by selection pressures and random drift, which fails to address rapid adaptive changes by host immune and antiviral pressures. The Near Neutral Balanced Selection Theory (NNBST) accounts for the interplay between minor advantageous and deleterious mutations and strong adaptive changes, making a possible better evolutionary model.A reference genomic sequence was used to establish ZIKV's relative substitution rate for every nucleotide based on reported viral mutation and substitution rates.Evaluation of each nucleotide's relative substitution rate (c/µ) should reveal an L-shaped probability distribution curve predicted by NBST for each site. Determination of non-synonymous (Ka, mutations change protein sequence) and synonymous (Ks, mutations do not change protein sequence) and the Ka/Ks ratio will also be determined. Comprehensive analysis of c/µ and Kq/Ks could shed light on the applicability of NNBST as a more accurate molecular evolutionary theory resulting in the enhancement of vaccine development and control strategies.

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