Dating the Common Ancestor from an NCBI Tree of 83688 High-Quality and Full-Length SARS-CoV-2 Genomes

The Emergence and Evolution of SARS-CoV-2

The origin of SARS-CoV-2 has evoked heated debate and strong accusations, yet seemingly little resolution. I review the scientific evidence on the origin of SARS-CoV-2 and its subsequent spread through the human population. The available data clearly point to a natural zoonotic emergence within, or closely linked to, the Huanan Seafood Wholesale Market in Wuhan. There is no direct evidence linking the emergence of SARS-CoV-2 to laboratory work conducted at the Wuhan Institute of Virology. The subsequent global spread of SARS-CoV-2 was characterized by a gradual adaptation to humans, with dual increases in transmissibility and virulence until the emergence of the Omicron variant. Of note has been the frequent transmission of SARS-CoV-2 from humans to other animals, marking it as a strongly host generalist virus. Unless lessons from the origin of SARS-CoV-2 are learned, it is inevitable that more zoonotic events leading to more epidemics and pandemics will plague human populations.

Higher Levels of SARS-CoV-2 Genetic Variation in Immunocompromised Patients: A Retrospective Case-Control Study

BACKGROUND

A severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection lasts longer in immunocompromised hosts than in immunocompetent patients. Prolonged infection is associated with a higher probability of selection for novel SARS-CoV-2 mutations, particularly in the spike protein, a critical target for vaccines and therapeutics.

METHODS

From December 2020 to September 2022, respiratory samples from 444 immunocompromised patients and 234 health care workers positive for SARS-CoV-2, diagnosed at 2 hospitals in Paris, France, were analyzed using whole-genome sequencing using Nanopore technology. Custom scripts were developed to assess the SARS-CoV-2 genetic diversity between the 2 groups and within the host.

RESULTS

Most infections were SARS-CoV-2 Delta or Omicron lineages. Viral genetic diversity was significantly higher in infections of immunocompromised patients than those of controls. Minor mutations were identified in viruses sequenced from immunocompromised individuals, which became signature mutations for newer SARS-CoV-2 variants as the epidemic progressed. Two patients were coinfected with Delta and Omicron variants. The follow-up of immunocompromised patients revealed that the SARS-CoV-2 genome evolution differed in the upper and lower respiratory tracts.

CONCLUSIONS

This study found that SARS-CoV-2 infection in immunocompromised patients is associated with higher genetic diversity, which could lead to the emergence of new SARS-CoV-2 variants with possible immune evasion or different virulence characteristics.

Rooting and Dating Large SARS-CoV-2 Trees by Modeling Evolutionary Rate as a Function of Time

Almost all published rooting and dating studies on SARS-CoV-2 assumed that (1) evolutionary rate does not change over time although different lineages can have different evolutionary rates (uncorrelated relaxed clock), and (2) a zoonotic transmission occurred in Wuhan and the culprit was immediately captured, so that only the SARS-CoV-2 genomes obtained in 2019 and the first few months of 2020 (resulting from the first wave of the global expansion from Wuhan) are sufficient for dating the common ancestor. Empirical data contradict the first assumption. The second assumption is not warranted because mounting evidence suggests the presence of early SARS-CoV-2 lineages cocirculating with the Wuhan strains. Large trees with SARS-CoV-2 genomes beyond the first few months are needed to increase the likelihood of finding SARS-CoV-2 lineages that might have originated at the same time as (or even before) those early Wuhan strains. I extended a previously published rapid rooting method to model evolutionary rate as a linear function instead of a constant. This substantially improves the dating of the common ancestor of sampled SARS-CoV-2 genomes. Based on two large trees with 83,688 and 970,777 high-quality and full-length SARS-CoV-2 genomes that contain complete sample collection dates, the common ancestor was dated to 12 June 2019 and 7 July 2019 with the two trees, respectively. The two data sets would give dramatically different or even absurd estimates if the rate was treated as a constant. The large trees were also crucial for overcoming the high rate-heterogeneity among different viral lineages. The improved method was implemented in the software TRAD.

RNA structure-altering mutations underlying positive selection on Spike protein reveal novel putative signatures to trace crossing host-species barriers in Betacoronavirus

Similar to other RNA viruses, the emergence of Betacoronavirus relies on cross-species viral transmission, which requires careful health surveillance monitoring of protein-coding information as well as genome-wide analysis. Although the evolutionary jump from natural reservoirs to humans may be mainly traced-back by studying the effect that hotspot mutations have on viral proteins, it is largely unexplored if other impacts might emerge on the structured RNA genome of Betacoronavirus. In this survey, the protein-coding and viral genome architecture were simultaneously studied to uncover novel insights into cross-species horizontal transmission events. We analysed 1,252,952 viral genomes of SARS-CoV, MERS-CoV, and SARS-CoV-2 distributed across the world in bats, intermediate animals, and humans to build a new landscape of changes in the RNA viral genome. Phylogenetic analyses suggest that bat viruses are the most closely related to the time of most recent common ancestor of Betacoronavirus, and missense mutations in viral proteins, mainly in the S protein S1 subunit: SARS-CoV (G > T; A577S); MERS-CoV (C > T; S746R and C > T; N762A); and SARS-CoV-2 (A > G; D614G) appear to have driven viral diversification. We also found that codon sites under positive selection on S protein overlap with non-compensatory mutations that disrupt secondary RNA structures in the RNA genome complement. These findings provide pivotal factors that might be underlying the eventual jumping the species barrier from bats to intermediate hosts. Lastly, we discovered that nearly half of the Betacoronavirus genomes carry highly conserved RNA structures, and more than 90% of these RNA structures show negative selection signals, suggesting essential functions in the biology of Betacoronavirus that have not been investigated to date. Further research is needed on negatively selected RNA structures to scan for emerging functions like the potential of coding virus-derived small RNAs and to develop new candidate antiviral therapeutic strategies.

Molecular evidence for SARS-CoV-2 in samples collected from patients with morbilliform eruptions since late 2019 in Lombardy, northern Italy

As a reference laboratory for measles and rubella surveillance in Lombardy, we evaluated the association between SARS-CoV-2 infection and measles-like syndromes, providing preliminary evidence for undetected early circulation of SARS-CoV-2. Overall, 435 samples from 156 cases were investigated. RNA from oropharyngeal swabs (N = 148) and urine (N = 141) was screened with four hemi-nested PCRs and molecular evidence for SARS-CoV-2 infection was found in 13 subjects. Two of the positive patients were from the pandemic period (2/12, 16.7%, March 2020-March 2021) and 11 were from the pre-pandemic period (11/44, 25%, August 2019-February 2020). Sera (N = 146) were tested for anti-SARS-CoV-2 IgG, IgM, and IgA antibodies. Five of the RNA-positive individuals also had detectable anti-SARS-CoV-2 antibodies. No strong evidence of infection was found in samples collected between August 2018 and July 2019 from 100 patients. The earliest sample with evidence of SARS-CoV-2 RNA was from September 12, 2019, and the positive patient was also positive for anti-SARS-CoV-2 antibodies (IgG and IgM). Mutations typical of B.1 strains previously reported to have emerged in January 2020 (C3037T, C14408T, and A23403G), were identified in samples collected as early as October 2019 in Lombardy. One of these mutations (C14408T) was also identified among sequences downloaded from public databases that were obtained by others from samples collected in Brazil in November 2019. We conclude that a SARS-CoV-2 progenitor capable of producing a measles-like syndrome may have emerged in late June-late July 2019 and that viruses with mutations characterizing B.1 strain may have been spreading globally before the first Wuhan outbreak. Our findings should be complemented by high-throughput sequencing to obtain additional sequence information. We highlight the importance of retrospective surveillance studies in understanding the early dynamics of COVID-19 spread and we encourage other groups to perform retrospective investigations to seek confirmatory proofs of early SARS-CoV-2 circulation.

The twin-beginnings of COVID-19 in Asia and Europe-one prevails quickly

In the spread of SARS-CoV-2, there have been multiple waves of replacement between strains, each of which having a distinct set of mutations. The first wave is a group of four mutations (C241T, C3037T, C14408T and A23403G [this being the amino acid change D614G]; all designated 0 to 1 below). This DG (D614G) group, fixed at the start of the pandemic, is the foundation of all subsequent waves of strains. Curiously, the DG group is absent in early Asian samples but present (and likely common) in Europe from the beginning. European data show that the high fitness of DG1111 requires the synergistic effect of all four mutations. However, the European strains would have had no time to evolve the four DG mutations (0 to 1), had they come directly from the early Asian DG0000 strain. Very likely, the European DG1111 strain had acquired the highly adaptive DG mutations in pre-pandemic Europe and had been spreading in parallel with the Asian strains. Two recent reports further support this twin-beginning interpretation. There was a period of two-way spread between Asia and Europe but, by May 2020, the European strains had supplanted the Asian strains globally. This large-scale replacement of one set of mutations for another has since been replayed many times as COVID-19 progresses.

SARS-CoV-2: tracing the origin, tracking the evolution

The origin of SARS-CoV-2 is uncertain. Findings support a "bat origin" but results are not highly convincing. Studies found evidence that SARS-CoV-2 was around for many years before the pandemic outbreak. Evidence has been published that the progenitor of SARS-CoV-2 already had the capability to bind strongly to the human ACE2 receptor. This may be an indication that many other animal viruses are capable to jump to humans, having already affinity for a human receptor. This is quite worrying since current ecosystems' collapse brings people to high proximity with animals, increasing probabilities for random viral transitions. On the other hand, future adaptation of SARS-CoV-2 is of great concern. Virus-host interactions are complicated and unfortunately, we still do not have accurate tools for predicting viruses' future evolution. Viral adaptation is a multifactorial process and probably SARS-CoV-2 will not become soon, as we wish, a harmless infection. However, humanity is currently under the largest vaccination program and it's of great interest to see if vaccinations will change the evolutionary game against the virus.

The Runaway Evolution of SARS-CoV-2 Leading to the Highly Evolved Delta Strain

In new epidemics after the host shift, the pathogens may experience accelerated evolution driven by novel selective pressures. When the accelerated evolution enters a positive feedback loop with the expanding epidemics, the pathogen's runaway evolution may be triggered. To test this possibility in coronavirus disease 2019 (COVID-19), we analyze the extensive databases and identify five major waves of strains, one replacing the previous one in 2020-2021. The mutations differ entirely between waves and the number of mutations continues to increase, from 3-4 to 21-31. The latest wave in the fall of 2021 is the Delta strain which accrues 31 new mutations to become highly prevalent. Interestingly, these new mutations in Delta strain emerge in multiple stages with each stage driven by 6-12 coding mutations that form a fitness group. In short, the evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from the oldest to the youngest wave, and from the earlier to the later stages of the Delta wave, is a process of acceleration with more and more mutations. The global increase in the viral population size (M(t), at time t) and the mutation accumulation (R(t)) may have indeed triggered the runaway evolution in late 2020, leading to the highly evolved Alpha and then Delta strain. To suppress the pandemic, it is crucial to break the positive feedback loop between M(t) and R(t), neither of which has yet to be effectively dampened by late 2021. New waves after Delta, hence, should not be surprising.

Waiting for the truth: is reluctance in accepting an early origin hypothesis for SARS-CoV-2 delaying our understanding of viral emergence?

Two years after the start of the COVID-19 pandemic, key questions about the emergence of its aetiological agent (SARS-CoV-2) remain a matter of considerable debate. Identifying when SARS-CoV-2 began spreading among people is one of those questions. Although the current canonically accepted timeline hypothesises viral emergence in Wuhan, China, in November or December 2019, a growing body of diverse studies provides evidence that the virus may have been spreading worldwide weeks, or even months, prior to that time. However, the hypothesis of earlier SARS-CoV-2 circulation is often dismissed with prejudicial scepticism and experimental studies pointing to early origins are frequently and speculatively attributed to false-positive tests. In this paper, we critically review current evidence that SARS-CoV-2 had been circulating prior to December of 2019, and emphasise how, despite some scientific limitations, this hypothesis should no longer be ignored and considered sufficient to warrant further larger-scale studies to determine its veracity.

Post-Alignment Adjustment and Its Automation

Multiple sequence alignment (MSA) is the basis for almost all sequence comparison and molecular phylogenetic inferences. Large-scale genomic analyses are typically associated with automated progressive MSA without subsequent manual adjustment, which itself is often error-prone because of the lack of a consistent and explicit criterion. Here, I outlined several commonly encountered alignment errors that cannot be avoided by progressive MSA for nucleotide, amino acid, and codon sequences. Methods that could be automated to fix such alignment errors were then presented. I emphasized the utility of position weight matrix as a new tool for MSA refinement and illustrated its usage by refining the MSA of nucleotide and amino acid sequences. The main advantages of the position weight matrix approach include (1) its use of information from all sequences, in contrast to other commonly used methods based on pairwise alignment scores and inconsistency measures, and (2) its speedy computation, making it suitable for a large number of long viral genomic sequences.