Evolution of the SARS-CoV-2 Mutational Spectrum

Modulation of biophysical properties of nucleocapsid protein in the mutant spectrum of SARS-CoV-2

Genetic diversity is a hallmark of RNA viruses and the basis for their evolutionary success. Taking advantage of the uniquely large genomic database of SARS-CoV-2, we examine the impact of mutations across the spectrum of viable amino acid sequences on the biophysical phenotypes of the highly expressed and multifunctional nucleocapsid protein. We find variation in the physicochemical parameters of its extended intrinsically disordered regions (IDRs) sufficient to allow local plasticity, but also observe functional constraints that similarly occur in related coronaviruses. In biophysical experiments with several N-protein species carrying mutations associated with major variants, we find that point mutations in the IDRs can have nonlocal impact and modulate thermodynamic stability, secondary structure, protein oligomeric state, particle formation, and liquid-liquid phase separation. In the Omicron variant, distant mutations in different IDRs have compensatory effects in shifting a delicate balance of interactions controlling protein assembly properties, and include the creation of a new protein-protein interaction interface in the N-terminal IDR through the defining P13L mutation. A picture emerges where genetic diversity is accompanied by significant variation in biophysical characteristics of functional N-protein species, in particular in the IDRs.

Role of N343 glycosylation on the SARS-CoV-2 S RBD structure and co-receptor binding across variants of concern

Glycosylation of the SARS-CoV-2 spike (S) protein represents a key target for viral evolution because it affects both viral evasion and fitness. Successful variations in the glycan shield are difficult to achieve though, as protein glycosylation is also critical to folding and structural stability. Within this framework, the identification of glycosylation sites that are structurally dispensable can provide insight into the evolutionary mechanisms of the shield and inform immune surveillance. In this work, we show through over 45 μs of cumulative sampling from conventional and enhanced molecular dynamics (MD) simulations, how the structure of the immunodominant S receptor binding domain (RBD) is regulated by N-glycosylation at N343 and how this glycan's structural role changes from WHu-1, alpha (B.1.1.7), and beta (B.1.351), to the delta (B.1.617.2), and omicron (BA.1 and BA.2.86) variants. More specifically, we find that the amphipathic nature of the N-glycan is instrumental to preserve the structural integrity of the RBD hydrophobic core and that loss of glycosylation at N343 triggers a specific and consistent conformational change. We show how this change allosterically regulates the conformation of the receptor binding motif (RBM) in the WHu-1, alpha, and beta RBDs, but not in the delta and omicron variants, due to mutations that reinforce the RBD architecture. In support of these findings, we show that the binding of the RBD to monosialylated ganglioside co-receptors is highly dependent on N343 glycosylation in the WHu-1, but not in the delta RBD, and that affinity changes significantly across VoCs. Ultimately, the molecular and functional insight we provide in this work reinforces our understanding of the role of glycosylation in protein structure and function and it also allows us to identify the structural constraints within which the glycosylation site at N343 can become a hotspot for mutations in the SARS-CoV-2 S glycan shield.

Mapping the Evolutionary Space of SARS-CoV-2 Variants to Anticipate Emergence of Subvariants Resistant to COVID-19 Therapeutics

New sublineages of SARS-CoV-2 variants-of-concern (VOCs) continuously emerge with mutations in the spike glycoprotein. In most cases, the sublineage-defining mutations vary between the VOCs. It is unclear whether these differences reflect lineage-specific likelihoods for mutations at each spike position or the stochastic nature of their appearance. Here we show that SARS-CoV-2 lineages have distinct evolutionary spaces (a probabilistic definition of the sequence states that can be occupied by expanding virus subpopulations). This space can be accurately inferred from the patterns of amino acid variability at the whole-protein level. Robust networks of co-variable sites identify the highest-likelihood mutations in new VOC sublineages and predict remarkably well the emergence of subvariants with resistance mutations to COVID-19 therapeutics. Our studies reveal the contribution of low frequency variant patterns at heterologous sites across the protein to accurate prediction of the changes at each position of interest.

Effect of molnupiravir on SARS-CoV-2 evolution in immunocompromised patients: a retrospective observational study

INTRODUCTION

Continued SARS-CoV-2 infection among immunocompromised individuals is likely to play a role in generating genomic diversity and the emergence of novel variants. Antiviral treatments such as molnupiravir are used to mitigate severe COVID-19 outcomes, but the extended effects of these drugs on viral evolution in patients with chronic infections remain uncertain. This study investigates how molnupiravir affects SARS-CoV-2 evolution in immunocompromised patients with prolonged infections.

METHODS

The study included five immunocompromised patients treated with molnupiravir and four patients not treated with molnupiravir (two immunocompromised and two non-immunocompromised). We selected patients who had been infected by similar SARS-CoV-2 variants and with high-quality genomes across timepoints to allow comparison between groups. Throat and nasopharyngeal samples were collected in patients up to 44 days post treatment and were sequenced using tiled amplicon sequencing followed by variant calling. The UShER pipeline and University of California Santa Cruz genome viewer provided insights into the global context of variants. Treated and untreated patients were compared, and mutation profiles were visualised to understand the impact of molnupiravir on viral evolution.

FINDINGS

Patients treated with molnupiravir showed a large increase in low-to-mid-frequency variants in as little as 10 days after treatment, whereas no such change was observed in untreated patients. Some of these variants became fixed in the viral population, including non-synonymous mutations in the spike protein. The variants were distributed across the genome and included unique mutations not commonly found in global omicron genomes. Notably, G-to-A and C-to-T mutations dominated the mutational profile of treated patients, persisting up to 44 days post treatment.

INTERPRETATION

Molnupiravir treatment in immunocompromised patients led to the accumulation of a distinctive pattern of mutations beyond the recommended 5 days of treatment. Treated patients maintained persistent PCR positivity for the duration of monitoring, indicating clear potential for transmission and subsequent emergence of novel variants.

FUNDING

Australian Research Council.

Molnupiravir increases SARS-CoV-2 genome diversity and complexity: A case-control cohort study

Molnupiravir, an oral direct-acting antiviral effective in vitro against SARS-CoV-2, has been largely employed during the COVID-19 pandemic, since December 2021. After marketing and widespread usage, a progressive increase in SARS-CoV-2 lineages characterized by a higher transition/transversion ratio, a characteristic signature of molnupiravir action, appeared in the Global Initiative on Sharing All Influenza Data (GISAID) and International Nucleotide Sequence Database Collaboration (INSDC) databases. Here, we assessed the drug effects by SARS-CoV-2 whole-genome sequencing on 38 molnupiravir-treated persistently positive COVID-19 outpatients tested before and after treatment. Seventeen tixagevimab/cilgavimab-treated outpatients served as controls. Mutational analyses confirmed that SARS-CoV-2 exhibits an increased transition/transversion ratio seven days after initiation of molnupiravir. Moreover we observed an increased G->A ratio compared to controls, which was not related to apolipoprotein B mRNAediting enzyme, catalytic polypeptide-like (APOBEC) activity. In addition, we demonstrated for the first time an increased diversity and complexity of the viral quasispecies.

Deciphering infected cell types, hub gene networks and cell-cell communication in infectious bronchitis virus via single-cell RNA sequencing

Infectious bronchitis virus (IBV) is a coronavirus that infects chickens, which exhibits a broad tropism for epithelial cells, infecting the tracheal mucosal epithelium, intestinal mucosal epithelium, and renal tubular epithelial cells. Utilizing single-cell RNA sequencing (scRNA-seq), we systematically examined cells in renal, bursal, and tracheal tissues following IBV infection and identified tissue-specific molecular markers expressed in distinct cell types. We evaluated the expression of viral RNA in diverse cellular populations and subsequently ascertained that distal tubules and collecting ducts within the kidney, bursal mucosal epithelial cells, and follicle-associated epithelial cells exhibit susceptibility to IBV infection through immunofluorescence. Furthermore, our findings revealed an upregulation in the transcription of proinflammatory cytokines IL18 and IL1B in renal macrophages as well as increased expression of apoptosis-related gene STAT in distal tubules and collecting duct cells upon IBV infection leading to renal damage. Cell-to-cell communication unveiled potential interactions between diverse cell types, as well as upregulated signaling pathways and key sender-receiver cell populations after IBV infection. Integrating single-cell data from all tissues, we applied weighted gene co-expression network analysis (WGCNA) to identify gene modules that are specifically expressed in different cell populations. Based on the WGCNA results, we identified seven immune-related gene modules and determined the differential expression pattern of module genes, as well as the hub genes within these modules. Our comprehensive data provides valuable insights into the pathogenesis of IBV as well as avian antiviral immunology.

Emergence of SARS-CoV-2 Omicron Variant JN.1 in Tamil Nadu, India - Clinical Characteristics and Novel Mutations

In December 2023, we observed a notable shift in the COVID-19 landscape, when the JN.1 emerged as a predominant SARS-CoV-2 variant with a 95% incidence. We characterized the clinical profile, and genetic changes in JN.1, an emerging SARS-CoV-2 variant of interest. Whole genome sequencing was performed on SARS-CoV-2 positive samples, followed by sequence analysis. Mutations within the spike protein sequences were analyzed and compared with the previous lineages and sublineages of SARS-CoV-2, to identify the potential impact of these unique mutations on protein structure and possible functionality. Several unique and dynamic mutations were identified herein. Our data provides key insights into the emergence of newer variants of SARS-CoV-2 in our region and highlights the need for robust and sustained genomic surveillance of SARS-CoV-2.

Properties and Mechanisms of Deletions, Insertions, and Substitutions in the Evolutionary History of SARS-CoV-2

SARS-CoV-2 has accumulated many mutations since its emergence in late 2019. Nucleotide substitutions leading to amino acid replacements constitute the primary material for natural selection. Insertions, deletions, and substitutions appear to be critical for coronavirus's macro- and microevolution. Understanding the molecular mechanisms of mutations in the mutational hotspots (positions, loci with recurrent mutations, and nucleotide context) is important for disentangling roles of mutagenesis and selection. In the SARS-CoV-2 genome, deletions and insertions are frequently associated with repetitive sequences, whereas C>U substitutions are often surrounded by nucleotides resembling the APOBEC mutable motifs. We describe various approaches to mutation spectra analyses, including the context features of RNAs that are likely to be involved in the generation of recurrent mutations. We also discuss the interplay between mutations and natural selection as a complex evolutionary trend. The substantial variability and complexity of pipelines for the reconstruction of mutations and the huge number of genomic sequences are major problems for the analyses of mutations in the SARS-CoV-2 genome. As a solution, we advocate for the development of a centralized database of predicted mutations, which needs to be updated on a regular basis.

Modulation of Biophysical Properties of Nucleocapsid Protein in the Mutant Spectrum of SARS-CoV-2

Genetic diversity is a hallmark of RNA viruses and the basis for their evolutionary success. Taking advantage of the uniquely large genomic database of SARS-CoV-2, we examine the impact of mutations across the spectrum of viable amino acid sequences on the biophysical phenotypes of the highly expressed and multifunctional nucleocapsid protein. We find variation in the physicochemical parameters of its extended intrinsically disordered regions (IDRs) sufficient to allow local plasticity, but also exhibiting functional constraints that similarly occur in related coronaviruses. In biophysical experiments with several N-protein species carrying mutations associated with major variants, we find that point mutations in the IDRs can have nonlocal impact and modulate thermodynamic stability, secondary structure, protein oligomeric state, particle formation, and liquid-liquid phase separation. In the Omicron variant, distant mutations in different IDRs have compensatory effects in shifting a delicate balance of interactions controlling protein assembly properties, and include the creation of a new protein-protein interaction interface in the N-terminal IDR through the defining P13L mutation. A picture emerges where genetic diversity is accompanied by significant variation in biophysical characteristics of functional N-protein species, in particular in the IDRs.

tANCHOR cell-based ELISA approach as a surrogate for antigen-coated plates to monitor specific IgG directed to the SARS-CoV-2 receptor-binding domain

Enzyme-linked immunosorbent assay (ELISA) systems use plates coated with peptides or expressed and purified proteins to monitor immunoglobulins derived from patient serum. However, there is currently no easy, flexible, and fast adaptive ELISA-based system for testing antibodies directed against new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. In this study, we utilized the tANCHOR protein display system that provides a cell surface decorated with the receptor-binding domain (RBD) to monitor specific antibodies derived from SARS-CoV-2 convalescent and vaccinated individuals directed against it. To test sera from vaccinees or convalescent individuals, only the RBD coding sequence needs to be cloned in the tANCHOR vector system and transfected into HeLa cells. Time-consuming protein expression, isolation, and purification followed by coating assay plates are not necessary. With this technique, the immune evasion of new SARS-CoV-2 variants from current vaccination regimes can be examined quickly and reliably.

Genomic Tools in Biological Invasions: Current State and Future Frontiers

Human activities are accelerating rates of biological invasions and climate-driven range expansions globally, yet we understand little of how genomic processes facilitate the invasion process. Although most of the literature has focused on underlying phenotypic correlates of invasiveness, advances in genomic technologies are showing a strong link between genomic variation and invasion success. Here, we consider the ability of genomic tools and technologies to (i) inform mechanistic understanding of biological invasions and (ii) solve real-world issues in predicting and managing biological invasions. For both, we examine the current state of the field and discuss how genomics can be leveraged in the future. In addition, we make recommendations pertinent to broader research issues, such as data sovereignty, metadata standards, collaboration, and science communication best practices that will require concerted efforts from the global invasion genomics community.

Mutational signature dynamics indicate SARS-CoV-2's evolutionary capacity is driven by host antiviral molecules

The COVID-19 pandemic has been characterised by sequential variant-specific waves shaped by viral, individual human and population factors. SARS-CoV-2 variants are defined by their unique combinations of mutations and there has been a clear adaptation to more efficient human infection since the emergence of this new human coronavirus in late 2019. Here, we use machine learning models to identify shared signatures, i.e., common underlying mutational processes and link these to the subset of mutations that define the variants of concern (VOCs). First, we examined the global SARS-CoV-2 genomes and associated metadata to determine how viral properties and public health measures have influenced the magnitude of waves, as measured by the number of infection cases, in different geographic locations using regression models. This analysis showed that, as expected, both public health measures and virus properties were associated with the waves of regional SARS-CoV-2 reported infection numbers and this impact varies geographically. We attribute this to intrinsic differences such as vaccine coverage, testing and sequencing capacity and the effectiveness of government stringency. To assess underlying evolutionary change, we used non-negative matrix factorisation and observed three distinct mutational signatures, unique in their substitution patterns and exposures from the SARS-CoV-2 genomes. Signatures 1, 2 and 3 were biased to C→T, T→C/A→G and G→T point mutations. We hypothesise assignments of these mutational signatures to the host antiviral molecules APOBEC, ADAR and ROS respectively. We observe a shift amidst the pandemic in relative mutational signature activity from predominantly Signature 1 changes to an increasingly high proportion of changes consistent with Signature 2. This could represent changes in how the virus and the host immune response interact and indicates how SARS-CoV-2 may continue to generate variation in the future. Linkage of the detected mutational signatures to the VOC-defining amino acids substitutions indicates the majority of SARS-CoV-2's evolutionary capacity is likely to be associated with the action of host antiviral molecules rather than virus replication errors.

Diversity of short linear interaction motifs in SARS-CoV-2 nucleocapsid protein

IMPORTANCE

Short linear motifs (SLiMs) are 3-10 amino acid long binding motifs in intrinsically disordered protein regions (IDRs) that serve as ubiquitous protein-protein interaction modules in eukaryotic cells. Through molecular mimicry, viruses hijack these sequence motifs to control host cellular processes. It is thought that the small size of SLiMs and the high mutation frequencies of viral IDRs allow rapid host adaptation. However, a salient characteristic of RNA viruses, due to high replication errors, is their obligate existence as mutant swarms. Taking advantage of the uniquely large genomic database of SARS-CoV-2, here, we analyze the role of sequence diversity in the presentation of SLiMs, focusing on the highly abundant, multi-functional nucleocapsid protein. We find that motif mimicry is a highly dynamic process that produces an abundance of motifs transiently present in subsets of mutant species. This diversity allows the virus to efficiently explore eukaryotic motifs and evolve the host-virus interface.

A molnupiravir-associated mutational signature in global SARS-CoV-2 genomes

Molnupiravir, an antiviral medication widely used against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), acts by inducing mutations in the virus genome during replication. Most random mutations are likely to be deleterious to the virus and many will be lethal; thus, molnupiravir-induced elevated mutation rates reduce viral load1,2. However, if some patients treated with molnupiravir do not fully clear the SARS-CoV-2 infections, there could be the potential for onward transmission of molnupiravir-mutated viruses. Here we show that SARS-CoV-2 sequencing databases contain extensive evidence of molnupiravir mutagenesis. Using a systematic approach, we find that a specific class of long phylogenetic branches, distinguished by a high proportion of G-to-A and C-to-T mutations, are found almost exclusively in sequences from 2022, after the introduction of molnupiravir treatment, and in countries and age groups with widespread use of the drug. We identify a mutational spectrum, with preferred nucleotide contexts, from viruses in patients known to have been treated with molnupiravir and show that its signature matches that seen in these long branches, in some cases with onward transmission of molnupiravir-derived lineages. Finally, we analyse treatment records to confirm a direct association between these high G-to-A branches and the use of molnupiravir.

Evolution of the Mutation Spectrum Across a Mammalian Phylogeny

Although evolutionary biologists have long theorized that variation in DNA repair efficacy might explain some of the diversity of lifespan and cancer incidence across species, we have little data on the variability of normal germline mutagenesis outside of humans. Here, we shed light on the spectrum and etiology of mutagenesis across mammals by quantifying mutational sequence context biases using polymorphism data from thirteen species of mice, apes, bears, wolves, and cetaceans. After normalizing the mutation spectrum for reference genome accessibility and k-mer content, we use the Mantel test to deduce that mutation spectrum divergence is highly correlated with genetic divergence between species, whereas life history traits like reproductive age are weaker predictors of mutation spectrum divergence. Potential bioinformatic confounders are only weakly related to a small set of mutation spectrum features. We find that clock-like mutational signatures previously inferred from human cancers cannot explain the phylogenetic signal exhibited by the mammalian mutation spectrum, despite the ability of these signatures to fit each species' 3-mer spectrum with high cosine similarity. In contrast, parental aging signatures inferred from human de novo mutation data appear to explain much of the 1-mer spectrum's phylogenetic signal in combination with a novel mutational signature. We posit that future models purporting to explain the etiology of mammalian mutagenesis need to capture the fact that more closely related species have more similar mutation spectra; a model that fits each marginal spectrum with high cosine similarity is not guaranteed to capture this hierarchy of mutation spectrum variation among species.

Fitness effects of mutations to SARS-CoV-2 proteins

Knowledge of the fitness effects of mutations to SARS-CoV-2 can inform assessment of new variants, design of therapeutics resistant to escape, and understanding of the functions of viral proteins. However, experimentally measuring effects of mutations is challenging: we lack tractable lab assays for many SARS-CoV-2 proteins, and comprehensive deep mutational scanning has been applied to only two SARS-CoV-2 proteins. Here, we develop an approach that leverages millions of publicly available SARS-CoV-2 sequences to estimate effects of mutations. We first calculate how many independent occurrences of each mutation are expected to be observed along the SARS-CoV-2 phylogeny in the absence of selection. We then compare these expected observations to the actual observations to estimate the effect of each mutation. These estimates correlate well with deep mutational scanning measurements. For most genes, synonymous mutations are nearly neutral, stop-codon mutations are deleterious, and amino acid mutations have a range of effects. However, some viral accessory proteins are under little to no selection. We provide interactive visualizations of effects of mutations to all SARS-CoV-2 proteins (https://jbloomlab.github.io/SARS2-mut-fitness/). The framework we describe is applicable to any virus for which the number of available sequences is sufficiently large that many independent occurrences of each neutral mutation are observed.

"Evolution of the mutation spectrum across a mammalian phylogeny"

Little is known about how the spectrum and etiology of germline mutagenesis might vary among mammalian species. To shed light on this mystery, we quantify variation in mutational sequence context biases using polymorphism data from thirteen species of mice, apes, bears, wolves, and cetaceans. After normalizing the mutation spectrum for reference genome accessibility and k -mer content, we use the Mantel test to deduce that mutation spectrum divergence is highly correlated with genetic divergence between species, whereas life history traits like reproductive age are weaker predictors of mutation spectrum divergence. Potential bioinformatic confounders are only weakly related to a small set of mutation spectrum features. We find that clocklike mutational signatures previously inferred from human cancers cannot explain the phylogenetic signal exhibited by the mammalian mutation spectrum, despite the ability of these clocklike signatures to fit each species' 3-mer spectrum with high cosine similarity. In contrast, parental aging signatures inferred from human de novo mutation data appear to explain much of the mutation spectrum's phylogenetic signal when fit to non-context-dependent mutation spectrum data in combination with a novel mutational signature. We posit that future models purporting to explain the etiology of mammalian mutagenesis need to capture the fact that more closely related species have more similar mutation spectra; a model that fits each marginal spectrum with high cosine similarity is not guaranteed to capture this hierarchy of mutation spectrum variation among species.