Evidence of SARS-CoV-2 convergent evolution in immunosuppressed patients treated with antiviral therapies.

BACKGROUND: The factors contributing to the accelerated convergent evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are not fully understood. Unraveling the contribution of viral replication in immunocompromised patients is important for the early detection of novel mutations and developing approaches to limit COVID-19. METHODS: We deep sequenced SARS-CoV-2 RNA from 192 patients (64% hospitalized, 39% immunosuppressed) and compared the viral genetic diversity within the patient groups of different immunity and hospitalization status. Serial sampling of 14 patients was evaluated for viral evolution in response to antiviral treatments. RESULTS: We identified hospitalized and immunosuppressed patients with significantly higher levels of viral genetic diversity and variability. Further evaluation of serial samples revealed accumulated mutations associated with escape from neutralizing antibodies in a subset of the immunosuppressed patients treated with antiviral therapies. Interestingly, the accumulated viral mutations that arose in this early Omicron wave, which were not common in the patient viral lineages, represent convergent mutations that are prevalent in the later Omicron sublineages, including the XBB, BA.2.86.1 and its descendent JN sublineages. CONCLUSIONS: Our results illustrate the importance of identifying convergent mutations generated during antiviral therapy in immunosuppressed patients, as they may contribute to the future evolutionary landscape of SARS-CoV-2. Our study also provides evidence of a correlation between SARS-CoV-2 convergent mutations and specific antiviral treatments. Evaluating high-confidence genomes from distinct waves in the pandemic with detailed patient metadata allows for discerning of convergent mutations that contribute to the ongoing evolution of SARS-CoV-2.

Phylogenetic network analysis of SARS-CoV-2 genomes.

In a phylogenetic network analysis of 160 complete human severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) genomes, we find three central variants distinguished by amino acid changes, which we have named A, B, and C, with A being the ancestral type according to the bat outgroup coronavirus. The A and C types are found in significant proportions outside East Asia, that is, in Europeans and Americans. In contrast, the B type is the most common type in East Asia, and its ancestral genome appears not to have spread outside East Asia without first mutating into derived B types, pointing to founder effects or immunological or environmental resistance against this type outside Asia. The network faithfully traces routes of infections for documented coronavirus disease 2019 (COVID-19) cases, indicating that phylogenetic networks can likewise be successfully used to help trace undocumented COVID-19 infection sources, which can then be quarantined to prevent recurrent spread of the disease worldwide.

Population Dynamics and Structural Effects at Short and Long Range Support the Hypothesis of the Selective Advantage of the G614 SARS-CoV-2 Spike Variant.

SARS-CoV-2 epidemics quickly propagated worldwide, sorting virus genomic variants in newly established propagules of infections. Stochasticity in transmission within and between countries or an actual selective advantage could explain the global high frequency reached by some genomic variants. Using statistical analyses, demographic reconstructions, and molecular dynamics simulations, we show that the globally invasive G614 spike variant 1) underwent a significant demographic expansion in most countries explained neither by stochastic effects nor by overrepresentation in clinical samples, 2) increases the spike S1/S2 furin-like site conformational plasticity (short-range effect), and 3) modifies the internal motion of the receptor-binding domain affecting its cross-connection with other functional domains (long-range effect). Our results support the hypothesis of a selective advantage at the basis of the spread of the G614 variant, which we suggest may be due to structural modification of the spike protein at the S1/S2 proteolytic site, and provide structural information to guide the design of variant-specific drugs.

The coSIR model predicts effective strategies to limit the spread of SARS-CoV-2 variants with low severity and high transmissibility.

Multiple new variants of SARS-CoV-2 have been identified as the COVID-19 pandemic spreads across the globe. However, most epidemic models view the virus as static and unchanging and thus fail to address the consequences of the potential evolution of the virus. Here, we built a competitive susceptible-infected-removed (coSIR) model to simulate the competition between virus strains of differing severities or transmissibility under various virus control policies. The coSIR model predicts that although the virus is extremely unlikely to evolve into a "super virus" that causes an increased fatality rate, virus variants with less severe symptoms can lead to potential new outbreaks and can cost more lives over time. The present model also demonstrates that the protocols restricting the transmission of the virus, such as wearing masks and social distancing, are the most effective strategy in reducing total mortality. A combination of adequate testing and strict quarantine is a powerful alternative to policies such as mandatory stay-at-home orders, which may have an enormous negative impact on the economy. In addition, building Mobile Cabin Hospitals can be effective and efficient in reducing the mortality rate of highly infectious virus strains. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11071-021-06705-8.

On the SARS-CoV-2 Variants.

The evolutionary dynamics of viruses, particularly exemplified by SARS-CoV-2 during the ongoing COVID-19 pandemic, underscore the intricate interplay between genetics, host adaptation, and viral spread. This paper delves into the genetic evolution of SARS-CoV-2, emphasizing the implications of viral variants on global health. Initially emerging from the Wuhan-Hu-1 lineage, SARS-CoV-2 rapidly diversified into numerous variants, each characterized by distinct mutations in the spike protein and other genomic regions. Notable variants such as B.1.1.7 (α), B.1.351 (ß), P.1 (γ), B.1.617.2 (δ), and the Omicron variant have garnered significant attention due to their heightened transmissibility and immune evasion capabilities. In particular, the Omicron variant has presented a myriad of subvariants, raising concerns about its potential impact on public health. Despite the emergence of numerous variants, the vast majority have exhibited limited expansion capabilities and have not posed significant threats akin to early pandemic strains. Continued genomic surveillance is imperative to identify emerging variants of concern promptly. While genetic adaptation is intrinsic to viral evolution, effective public health responses must be grounded in empirical evidence to navigate the evolving landscape of the pandemic with resilience and precision.

SARS-CoV-2 infection in immunosuppression evolves sub-lineages which independently accumulate neutralization escape mutations.

One mechanism of variant formation may be evolution during long-term infection in immunosuppressed people. To understand the viral phenotypes evolved during such infection, we tested SARS-CoV-2 viruses evolved from an ancestral B.1 lineage infection lasting over 190 days post-diagnosis in an advanced HIV disease immunosuppressed individual. Sequence and phylogenetic analysis showed two evolving sub-lineages, with the second sub-lineage replacing the first sub-lineage in a seeming evolutionary sweep. Each sub-lineage independently evolved escape from neutralizing antibodies. The most evolved virus for the first sub-lineage (isolated day 34) and the second sub-lineage (isolated day 190) showed similar escape from ancestral SARS-CoV-2 and Delta-variant infection elicited neutralizing immunity despite having no spike mutations in common relative to the B.1 lineage. The day 190 isolate also evolved higher cell-cell fusion and faster viral replication and caused more cell death relative to virus isolated soon after diagnosis, though cell death was similar to day 34 first sub-lineage virus. These data show that SARS-CoV-2 strains in prolonged infection in a single individual can follow independent evolutionary trajectories which lead to neutralization escape and other changes in viral properties.

SARS-CoV-2 nonstructural protein 6 from Alpha to Omicron: evolution of a transmembrane protein.

We recently reported that mutations in both the spike glycoprotein and nonstructural protein 6 (nsp6) were associated with attenuation of the SARS-CoV-2 Omicron BA.1 variant. While mutations in spike allow evasion of neutralizing antibodies and promote specific modes of viral entry, the role of nsp6 mutations in pathogenesis is less clear. Nsp6 is essential for modifying the endoplasmic reticulum and generating double-membrane vesicles, the site of viral RNA replication. To investigate the evolution of nsp6, we evaluated 91,596 high-confidence human SARS-CoV-2 whole-genome sequences across 19 variants and lineages. While nsp6 of early variants of concern, such as Alpha, Beta, and Gamma, carried a triple amino acid deletion (106-108, termed ΔSGF), the Delta, Epsilon, and Mu lineages retained the ancestral nsp6 sequence. For nsp6 in the emerging Omicron variants, we report a transition from an amino acid 105-107 ΔLSG deletion in BA.1 to increased dominance of the ΔSGF in BA.2 and subsequent lineages. Our findings indicate that deletion within nsp6 was independently selected in multiple lineages of SARS-CoV-2, both early and late in the pandemic. Analysis of SARS-CoV-2-related coronaviruses in bats and pangolins revealed nsp6 sequences similar to the ancestral SARS-CoV-2 virus, indicating that the deletion in nsp6 may be an adaptation to replication in humans. Analysis of nsp6 sequences from multiple coronaviruses predicts a multipass transmembrane protein with a conserved C-terminal domain. Monitoring and evaluating changes in nsp6 and other nonstructural proteins will contribute to our understanding of factors associated with the attenuation of pandemic coronaviruses. IMPORTANCE There is an ongoing need to evaluate genetic changes in SARS-CoV-2 for effects on transmission and pathogenesis. We recently reported an unexpected role for replicase component nsp6, in addition to changes in spike, in the attenuation of Omicron BA.1. In this commentary, we document a triple-amino-acid deletion in a predicted lumenal domain of nsp6 that was found in multiple, independent variants of SARS-CoV-2, including all recent Omicron lineages. Furthermore, we modeled the predicted structure of nsp6, implicating a multipass transmembrane architecture as conserved in members of the Coronaviridae family. This information can guide future studies investigating the role of nsp6 in the pathogenesis of existing and emerging coronaviruses.

Analysis of Genomic Characteristics of SARS-CoV-2 in Italy, 29 January to 27 March 2020.

We performed next-generation sequencing (NGS), phylogenetic analysis, gene flows, and N- and O-glycosylation prediction on SARS-CoV-2 genomes collected from lab-confirmed cases from different Italian regions. To this end, a total of 111 SARS-CoV-2 genomes collected in Italy between 29 January and 27 March 2020 were investigated. The majority of the genomes belonged to lineage B.1, with some descendant lineages. The gene flow analysis showed that the spread occurred mainly from the north to the center and to the south of Italy, as confirmed by epidemiological data. The mean evolutionary rate estimated here was 8.731 × 10-4 (95% highest posterior density, HPD intervals 5.809 × 10-4 to 1.19 × 10-3), in line with values reported by other authors. The dated phylogeny suggested that SARS-CoV-2 lineage B.1 probably entered Italy between the end of January and early February 2020. Continuous molecular surveillance is needed to trace virus circulation and evolution.

Complete Genomic Characterisation and Mutation Patterns of Iraqi SARS-CoV-2 Isolates.

This study was performed for molecular characterisation of the SARS-CoV-2 strains in Iraq and reveal their variants, lineages, clades, and mutation patterns. A total of 912 Iraqi sequences were retrieved from GISAID, which had been submitted from the beginning of the SARS-CoV-2 pandemic to 26 September 2022, along with 12 samples that were collected during the third and fifth waves of the SARS-CoV-2 pandemic. Next-generation sequencing was performed using an Illumina MiSeq system, and phylogenetic analysis was performed for all the Iraqi sequences retrieved from GISAID. Three established global platforms GISAID, Nextstrain, and PANGO were used for the classification of isolates into distinct clades, variants, and lineages. Analysis of the isolates of this study showed that all the sequences from the third wave were clustered in the GK clades and the 21J (Delta) clade according to the GISAID and Nextclade systems, while the PANGO system revealed that six sequences were B.1.617.2 and four sequences were of the AY.33 lineage. Furthermore, the latest e wave in the summer of 2022 was due to thpredominance of the BA.5.2 lineage of the 22B (Omicron) clade in Iraq. Our study revealed patterns of circulation and dominance of SARS-CoV-2 clades and their lineages in the subsequent pandemic waves in the country.

A Pre-Vaccination Baseline of SARS-CoV-2 Genetic Surveillance and Diversity in the United States.

COVID-19 vaccines were first administered on 15 December 2020, marking an important transition point for the spread of SARS-CoV-2 in the United States (U.S.). Prior to this point in time, the virus spread to an almost completely immunologically naïve population, whereas subsequently, vaccine-induced immune pressure and prior infections might be expected to influence viral evolution. Accordingly, we conducted a study to characterize the spread of SARS-CoV-2 in the U.S. pre-vaccination, investigate the depth and uniformity of genetic surveillance during this period, and measure and otherwise characterize changing viral genetic diversity, including by comparison with more recently emergent variants of concern (VOCs). In 2020, SARS-CoV-2 spread across the U.S. in three phases distinguishable by peaks in the numbers of infections and shifting geographical distributions. Virus was genetically sampled during this period at an overall rate of ~1.2%, though there was a substantial mismatch between case rates and genetic sampling nationwide. Viral genetic diversity tripled over this period but remained low in comparison to other widespread RNA virus pathogens, and although 54 amino acid changes were detected at frequencies exceeding 5%, linkage among them was not observed. Based on our collective observations, our analysis supports a targeted strategy for worldwide genetic surveillance as perhaps the most sensitive and efficient means of detecting new VOCs.

Lung organoid simulations for modelling and predicting the effect of mutations on SARS-CoV-2 infectivity.

The global pandemic caused by the SARS-CoV-2 virus continues to spread. Infection with SARS- CoV-2 causes COVID-19, a disease of variable severity. Mutation has already altered the SARS-CoV-2 genome from its original reported sequence and continued mutation is highly probable. These mutations can: (i) have no significant impact (they are silent), (ii) result in a complete loss or reduction of infectivity, or (iii) induce increase in infectivity. Physical generation, for research purposes, of viral mutations that could enhance infectivity are controversial and highly regulated. The primary purpose of this project was to evaluate the ability of the DeepNEU machine learning stem-cell simulation platform to enable rapid and efficient assessment of the potential impact of viral loss-of-function (LOF) and gain-of-function (GOF) mutations on SARS-CoV-2 infectivity. Our data suggest that SARS-CoV-2 infection can be simulated in human alveolar type lung cells. Simulation of infection in these lung cells can be used to model and assess the impact of LOF and GOF mutations in the SARS-CoV2 genome. We have also created a four- factor infectivity measure: the DeepNEU Case Fatality Rate (dnCFR). dnCFR can be used to assess infectivity based on the presence or absence of the key viral proteins (NSP3, Spike-RDB, N protein, and M protein). dnCFR was used in this study, not to only assess the impact of different mutations on SARS-CoV2 infectivity, but also to categorize the effects of mutations as loss of infectivity or gain of infectivity events.

Using primary literature on SARS-CoV-2 to promote student learning about evolution.

The ongoing COVID-19 pandemic caused by SARS-CoV-2 has caused widespread deaths, illnesses, and societal disruption. I describe here how I pivoted a discussion-based senior biology capstone course to include a multiweek module surrounding one primary literature paper on the evolution of SARS-CoV-2 and the subsequent scientific discourse about the paper. Using a gradual reveal of the paper following the CREATE method (consider, read, elucidate, and think of the next experiment), I challenged students to learn new evolutionary principles and critically analyze the data surrounding the evolution and transmission of SARS-CoV-2 presented in the paper. I also provide general advice for implementing this module in future courses.