Davidson Alma, Parr Marina, Totzeck Franziska, Churkin Alexander, Barash Danny, Frishman Dmitrij, Tuller Tamir
Department of Biomedical Engineering, Tel Aviv University, Tel Aviv 6997801, Israel.
Department of Bioinformatics, School of Life Sciences, Technical University of Munich, Freising, Germany.
Comput Struct Biotechnol J. 2025 May 20;27:2034-2050. doi: 10.1016/j.csbj.2025.05.021. eCollection 2025.
As viruses evolve over time with their host, they adapt to multiple cellular functions to ensure efficient long-term transmission. Their ability to survive and function efficiently depends on optimizing their genetic code to effectively recruit the host's gene expression machinery, particularly the translation machinery. Codon usage bias (CUB) measures the level of adaptation at the codon level, considering multiple factors such as the host's tRNA pool.By estimating the adaptation scores of viruses to their host, we can gain insight into the changes that occur on the genomic level throughout their evolution. In our study, we propose tracking the viral evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using CUB to estimate adaptation. By comparing different strains and analyzing changes over time, we demonstrate an increased adaptation of the Omicron SARS-COV-2 variant. In addition, we observe fluctuations in CUB scores, with periods of decreased and then increased adaptation over time, offering detailed insights at a fine temporal resolution. This analysis further contributes to understanding how different mutations influence viral adaptation, as well as the evolution of other human-infecting viruses.
随着病毒与其宿主长期共同进化,它们会适应多种细胞功能以确保高效的长期传播。它们有效存活和发挥功能的能力取决于优化其遗传密码,从而有效地利用宿主的基因表达机制,尤其是翻译机制。密码子使用偏好(CUB)在考虑宿主tRNA库等多种因素的情况下,衡量密码子水平的适应程度。通过估计病毒对其宿主的适应分数,我们可以深入了解病毒在整个进化过程中基因组水平上发生的变化。在我们的研究中,我们建议使用CUB来估计适应性,从而追踪严重急性呼吸综合征冠状病毒2(SARS-CoV-2)的病毒进化。通过比较不同毒株并分析随时间的变化,我们证明了奥密克戎SARS-CoV-2变体的适应性增强。此外,我们观察到CUB分数的波动,随着时间的推移,适应度会出现先下降后上升的时期,这在精细的时间分辨率上提供了详细的见解。该分析进一步有助于理解不同突变如何影响病毒适应性以及其他感染人类的病毒的进化。