Evolution of viral pathogens follows a linear order

TL;DR

This study uncovers a linear order in amino acid usage across key viral families, aiding in predicting mutations, understanding viral evolution, and informing vaccine development and outbreak source identification.

Contribution

It reveals a conserved linear pattern in amino acid usage among viruses, which can predict mutations and trace outbreak origins, advancing viral evolutionary understanding.

Findings

Amino acid usage follows a linear order within viral genomes.

Distribution of amino acids is closely related to viral species.

Pattern can predict future viral mutations and variants.

Abstract

Although lessons have been learned from previous severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) outbreaks, the rapid evolution of the viruses means that future outbreaks of a much larger scale are possible, as shown by the current coronavirus disease 2019 (COVID-19) outbreak. Therefore, it is necessary to better understand the evolution of coronaviruses as well as viruses in general. This study reports a comparative analysis of the amino acid usage within several key viral families and genera that are prone to triggering outbreaks, including coronavirus (SARS-CoV-2, SARS-CoV, MERS-CoV, HCoV-HKU1, HCoV-OC43, HCoV-NL63, HCoV-229E), influenza A (H1N1, H3N2), flavivirus (dengue virus serotypes 1-4, Zika) and ebolavirus (Zaire, Sudan, Bundibugyo ebolavirus). Our analysis reveals that the distribution of amino acid usage in the viral genome is constrained to follow a linear order, and the distribution remains closely related to the viral species within the family or genus. This constraint can be adapted to predict viral mutations and future variants of concern. By studying previous SARS and MERS outbreaks, we have adapted this naturally occurring pattern to determine that although pangolin plays a role in the outbreak of COVID-19, it may not be the sole agent as an intermediate animal. In addition to this study, our findings contribute to the understanding of viral mutations for subsequent development of vaccines and toward developing a model to determine the source of the outbreak.