Large-Scale Analysis of SARS-CoV-2 Synonymous Mutations Reveals the Adaptation to the Human Codon Usage During the Virus Evolution

The RdRp genotyping of SARS-CoV-2 isolated from patients with different clinical spectrum of COVID-19

BACKGROUND

The evolution of SARS-CoV-2 has been observed from the very beginning of the fight against COVID-19, some mutations are indicators of potentially dangerous variants of the virus. However, there is no clear association between the genetic variants of SARS-CoV-2 and the severity of COVID-19. We aimed to analyze the genetic variability of RdRp in correlation with different courses of COVID-19.

RESULTS

The prospective study included 77 samples of SARS-CoV-2 isolated from outpatients (1st degree of severity) and hospitalized patients (2nd, 3rd and 4th degree of severity). The retrospective analyses included 15,898,266 cases of SARS-CoV-2 genome sequences deposited in the GISAID repository. Single-nucleotide variants were identified based on the four sequenced amplified fragments of SARS-CoV-2. The analysis of the results was performed using appropriate statistical methods, with p < 0.05, considered statistically significant. Additionally, logistic regression analysis was performed to predict the strongest determinants of the observed relationships. The number of mutations was positively correlated with the severity of the COVID-19, and older male patients. We detected four mutations that significantly increased the risk of hospitalization of COVID-19 patients (14676C > T, 14697C > T, 15096 T > C, and 15279C > T), while the 15240C > T mutation was common among strains isolated from outpatients. The selected mutations were searched worldwide in the GISAID database, their presence was correlated with the severity of COVID-19.

CONCLUSION

Identified mutations have the potential to be used to assess the increased risk of hospitalization in COVID-19 positive patients. Experimental studies and extensive epidemiological data are needed to investigate the association between individual mutations and the severity of COVID-19.

Optimization and Deoptimization of Codons in SARS-CoV-2 and Related Implications for Vaccine Development

The spread of coronavirus disease 2019 (COVID-19), caused by severe respiratory syndrome coronavirus 2 (SARS-CoV-2), has progressed into a global pandemic. To date, thousands of genetic variants have been identified among SARS-CoV-2 isolates collected from patients. Sequence analysis reveals that the codon adaptation index (CAI) values of viral sequences have decreased over time but with occasional fluctuations. Through evolution modeling, it is found that this phenomenon may result from the virus's mutation preference during transmission. Using dual-luciferase assays, it is further discovered that the deoptimization of codons in the viral sequence may weaken protein expression during virus evolution, indicating that codon usage may play an important role in virus fitness. Finally, given the importance of codon usage in protein expression and particularly for mRNA vaccines, it is designed several codon-optimized Omicron BA.2.12.1, BA.4/5, and XBB.1.5 spike mRNA vaccine candidates and experimentally validated their high levels of expression. This study highlights the importance of codon usage in virus evolution and provides guidelines for codon optimization in mRNA and DNA vaccine development.

Molecular transition of SARS-CoV-2 from critical patients during the first year of the COVID-19 pandemic in Mexico City

Background

The SARS-CoV-2 virus has caused unprecedented mortality since its emergence in late 2019. The continuous evolution of the viral genome through the concerted action of mutational forces has produced distinct variants that became dominant, challenging human immunity and vaccine development.

Aim and methods

In this work, through an integrative genomic approach, we describe the molecular transition of SARS-CoV-2 by analyzing the viral whole genome sequences from 50 critical COVID-19 patients recruited during the first year of the pandemic in Mexico City.

Results

Our results revealed differential levels of the evolutionary forces across the genome and specific mutational processes that have shaped the first two epidemiological waves of the pandemic in Mexico. Through phylogenetic analyses, we observed a genomic transition in the circulating SARS-CoV-2 genomes from several lineages prevalent in the first wave to a dominance of the B.1.1.519 variant (defined by T478K, P681H, and T732A mutations in the spike protein) in the second wave.

Conclusion

This work contributes to a better understanding of the evolutionary dynamics and selective pressures that act at the genomic level, the prediction of more accurate variants of clinical significance, and a better comprehension of the molecular mechanisms driving the evolution of SARS-CoV-2 to improve vaccine and drug development.

Web Resources for SARS-CoV-2 Genomic Database, Annotation, Analysis and Variant Tracking

The SARS-CoV-2 genomic data continue to grow, providing valuable information for researchers and public health officials. Genomic analysis of these data sheds light on the transmission and evolution of the virus. To aid in SARS-CoV-2 genomic analysis, many web resources have been developed to store, collate, analyze, and visualize the genomic data. This review summarizes web resources used for the SARS-CoV-2 genomic epidemiology, covering data management and sharing, genomic annotation, analysis, and variant tracking. The challenges and further expectations for these web resources are also discussed. Finally, we highlight the importance and need for continued development and improvement of related web resources to effectively track the spread and understand the evolution of the virus.

Analysis of 3.5 million SARS-CoV-2 sequences reveals unique mutational trends with consistent nucleotide and codon frequencies

BACKGROUND

Since the onset of the SARS-CoV-2 pandemic, bioinformatic analyses have been performed to understand the nucleotide and synonymous codon usage features and mutational patterns of the virus. However, comparatively few have attempted to perform such analyses on a considerably large cohort of viral genomes while organizing the plethora of available sequence data for a month-by-month analysis to observe changes over time. Here, we aimed to perform sequence composition and mutation analysis of SARS-CoV-2, separating sequences by gene, clade, and timepoints, and contrast the mutational profile of SARS-CoV-2 to other comparable RNA viruses.

METHODS

Using a cleaned, filtered, and pre-aligned dataset of over 3.5 million sequences downloaded from the GISAID database, we computed nucleotide and codon usage statistics, including calculation of relative synonymous codon usage values. We then calculated codon adaptation index (CAI) changes and a nonsynonymous/synonymous mutation ratio (dN/dS) over time for our dataset. Finally, we compiled information on the types of mutations occurring for SARS-CoV-2 and other comparable RNA viruses, and generated heatmaps showing codon and nucleotide composition at high entropy positions along the Spike sequence.

RESULTS

We show that nucleotide and codon usage metrics remain relatively consistent over the 32-month span, though there are significant differences between clades within each gene at various timepoints. CAI and dN/dS values vary substantially between different timepoints and different genes, with Spike gene on average showing both the highest CAI and dN/dS values. Mutational analysis showed that SARS-CoV-2 Spike has a higher proportion of nonsynonymous mutations than analogous genes in other RNA viruses, with nonsynonymous mutations outnumbering synonymous ones by up to 20:1. However, at several specific positions, synonymous mutations were overwhelmingly predominant.

CONCLUSIONS

Our multifaceted analysis covering both the composition and mutation signature of SARS-CoV-2 gives valuable insight into the nucleotide frequency and codon usage heterogeneity of SARS-CoV-2 over time, and its unique mutational profile compared to other RNA viruses.

Natural selection pressure exerted on "Silent" mutations during the evolution of SARS-CoV-2: Evidence from codon usage and RNA structure

From the first emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) till now, multiple mutations that caused synonymous and nonsynonymous substitutions have accumulated. Among them, synonymous substitutions were regarded as "silent" mutations that received less attention than nonsynonymous substitutions that cause amino acid variations. However, the importance of synonymous substitutions can not be neglected. This research focuses on synonymous substitutions on SARS-CoV-2 and proves that synonymous substitutions were under purifying selection in its evolution. The evidence of purifying selection is provided by comparing the mutation number per site in coding and non-coding regions. We then study the two forces of purifying selection: synonymous codon usage and RNA secondary structure. Results show that the codon usage optimization leads to an adapted codon usage towards humans. Furthermore, our results show that the maintenance of RNA secondary structure causes the purifying of synonymous substitutions in the structural region. These results explain the selection pressure on synonymous substitutions during the evolution of SARS-CoV-2.

Attenuation and Degeneration of SARS-CoV-2 Despite Adaptive Evolution

The evolution of severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) has followed similar trends as other RNA viruses, such as human immunodeficiency virus type 1 and the influenza A virus. Rapid initial diversification was followed by strong competition and a rapid succession of dominant variants. Host-initiated RNA editing has been the primary mechanism for introducing mutations. A significant number of mutations detrimental to viral replication have been quickly purged. Fixed mutations are mostly diversifying mutations selected for host adaptation and immune evasion, with the latter accounting for the majority of the mutations. However, immune evasion often comes at the cost of functionality, and thus, optimal functionality is still far from being accomplished. Instead, selection for antibody-escaping variants and accumulation of near-neutral mutations have led to suboptimal codon usage and reduced replicative capacity, as demonstrated in non-respiratory cell lines. Beneficial adaptation of the virus includes reduced infectivity in lung tissues and increased tropism for the upper airway, resulting in shorter incubation periods, milder diseases, and more efficient transmission between people.

Characterization of SARS-CoV-2 Mutational Signatures from 1.5+ Million Raw Sequencing Samples

We present a large-scale analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) substitutions, considering 1,585,456 high-quality raw sequencing samples, aimed at investigating the existence and quantifying the effect of mutational processes causing mutations in SARS-CoV-2 genomes when interacting with the human host. As a result, we confirmed the presence of three well-differentiated mutational processes likely ruled by reactive oxygen species (ROS), apolipoprotein B editing complex (APOBEC), and adenosine deaminase acting on RNA (ADAR). We then evaluated the activity of these mutational processes in different continental groups, showing that some samples from Africa present a significantly higher number of substitutions, most likely due to higher APOBEC activity. We finally analyzed the activity of mutational processes across different SARS-CoV-2 variants, and we found a significantly lower number of mutations attributable to APOBEC activity in samples assigned to the Omicron variant.

The Rise and Fall of SARS-CoV-2 Variants and Ongoing Diversification of Omicron

In late December of 2019, high-throughput sequencing technologies enabled rapid identification of SARS-CoV-2 as the etiological agent of COVID-19, and global sequencing efforts are now a critical tool for monitoring the ongoing spread and evolution of this virus. Here, we provide a short retrospective analysis of SARS-CoV-2 variants by analyzing a subset (n = 97,437) of all publicly available SARS-CoV-2 genomes (n = ~11.9 million) that were randomly selected but equally distributed over the course of the pandemic. We plot the appearance of new variants of concern (VOCs) over time and show that the mutation rates in Omicron (BA.1) and Omicron sub-lineages (BA.2–BA.5) are significantly elevated compared to previously identified SARS-CoV-2 variants. Mutations in Omicron are primarily restricted to the spike and nucleocapsid proteins, while 24 other viral proteins—including those involved in SARS-CoV-2 replication—are generally conserved. Collectively, this suggests that the genetic distinction of Omicron primarily arose from selective pressures on the spike, and that the fidelity of replication of this variant has not been altered.

Covariance predicts conserved protein residue interactions important for the emergence and continued evolution of SARS-CoV-2 as a human pathogen

SARS-CoV-2 is one of three recognized coronaviruses (CoVs) that have caused epidemics or pandemics in the 21st century and that likely emerged from animal reservoirs. Differences in nucleotide and protein sequence composition within related β-coronaviruses are often used to better understand CoV evolution, host adaptation, and their emergence as human pathogens. Here we report the comprehensive analysis of amino acid residue changes that have occurred in lineage B β-coronaviruses that show covariance with each other. This analysis revealed patterns of covariance within conserved viral proteins that potentially define conserved interactions within and between core proteins encoded by SARS-CoV-2 related β-coronaviruses. We identified not only individual pairs but also networks of amino acid residues that exhibited statistically high frequencies of covariance with each other using an independent pair model followed by a tandem model approach. Using 149 different CoV genomes that vary in their relatedness, we identified networks of unique combinations of alleles that can be incrementally traced genome by genome within different phylogenic lineages. Remarkably, covariant residues and their respective regions most abundantly represented are implicated in the emergence of SARS-CoV-2 and are also enriched in dominant SARS-CoV-2 variants.

Host adaptation of codon usage in SARS-CoV-2 from mammals indicates potential natural selection and viral fitness

SARS-CoV-2 infection, which is the cause of the COVID-19 pandemic, has expanded across various animal hosts, and the virus can be transmitted particularly efficiently in minks. It is still not clear how SARS-CoV-2 is selected and evolves in its hosts, or how mutations affect viral fitness. In this report, sequences of SARS-CoV-2 isolated from human and animal hosts were analyzed, and the binding energy and capacity of the spike protein to bind human ACE2 and the mink receptor were compared. Codon adaptation index (CAI) analysis indicated the optimization of viral codons in some animals such as bats and minks, and a neutrality plot demonstrated that natural selection had a greater influence on some SARS-CoV-2 sequences than mutational pressure. Molecular dynamics simulation results showed that the mutations Y453F and N501T in mink SARS-CoV-2 could enhance the binding of the viral spike to the mink receptor, indicating the involvement of these mutations in natural selection and viral fitness. Receptor binding analysis revealed that the mink SARS-CoV-2 spike interacted more strongly with the mink receptor than the human receptor. Tracking the variations and codon bias of SARS-CoV-2 is helpful for understanding the fitness of the virus in virus transmission, pathogenesis, and immune evasion.