Abstract

The evolution of the SARS-CoV2 coronavirus S-protein is studied using a mass spectrometry based protein phylogenetic approach (known as phylonumerics). This is achieved using mass maps generated for the surface S-protein across various strains, including new variants, to construct phylogenetic trees. The trees are built solely from these numerical datasets through a pairwise comparison of mass values from each protein set. Single point mutations are calculated from peptide mass differences across different sets and these are displayed at the branch nodes on the trees in a single step tree-building step. The topology of the trees is studied with different protein coverages and the mutations identified are compared with those derived from the sequence data. It is demonstrated that most non-synonymous mutations can be correctly identified from the mass data alone, thus avoiding the need for gene or protein sequencing, and any sequence alignment, that are required by other phylogenetic approaches.

摘要

使用基于质谱的蛋白质系统发育方法（称为phylonumerics ）研究 SARS-CoV2 冠状病毒 S 蛋白的进化）。这是使用为各种菌株（包括新变体）的表面 S 蛋白生成的质量图来构建系统发育树来实现的。通过对每个蛋白质组的质量值进行成对比较，这些树完全由这些数字数据集构建而成。单点突变是根据不同组的肽质量差异计算得出的，这些突变在单步树构建步骤中显示在树上的分支节点上。用不同的蛋白质覆盖率研究树的拓扑结构，并将识别的突变与来自序列数据的突变进行比较。已经证明，仅从大量数据中就可以正确识别大多数非同义突变，从而避免了其他系统发育方法所需的基因或蛋白质测序以及任何序列比对的需要。