Patterns of within-host genetic diversity in SARS-CoV-2

SARS-CoV-2 biological clones are genetically heterogeneous and include clade-discordant residues

Defective genomes are part of SARS-CoV-2 quasispecies. High-resolution, ultra-deep sequencing of bulk RNA from viral populations does not distinguish RNA mutations, insertions, and deletions in viable genomes from those in defective genomes. To quantify SARS-CoV-2 infectious variant progeny, virus from four individual plaques (biological clones) of a preparation of isolate USA-WA1/2020, formed on Vero E6 cell monolayers, was subjected to further biological cloning to yield 9 second-generation and 15 third-generation sub-clones. Consensus genomic sequences of the biological clones and sub-clones included an average of 2.8 variations per viable genome, relative to the consensus sequence of the parental USA-WA1/2020 virus. This value is 6.5-fold lower than the estimates for biological clones of other RNA viruses such as bacteriophage Qβ, foot-and-mouth disease virus, or hepatitis C virus in cell culture. The mutant spectrum complexity of the nsp12 (polymerase)- and spike (S)-coding region was unique in the progeny of each of 10 third-generation sub-clones; they shared 2.4% of the total of 164 different mutations and deletions scored in the 3,719 genomic residues that were screened. The presence of minority out-of-frame deletions revealed the ease of defective genome production from an individual infectious genome. Several low-frequency point mutations and deletions were clade-discordant in that they were not typical of USA-WA1/2020 but served to define the consensus sequences of future SARS-CoV-2 clades. Implications for SARS-CoV-2 adaptability and COVID-19 control of the viable genome heterogeneity and the generation of complex mutant spectra from individual genomes are discussed.IMPORTANCESequencing of biological clones is a means to identify mutations, insertions, and deletions located in viable genomes. This distinction is particularly important for viral populations, such as those of SARS-CoV-2, that contain large proportions of defective genomes. By sequencing biological clones and sub-clones, we quantified the heterogeneity of the viable complement of USA-WA1/2020 to be lower than exhibited by other RNA viruses. This difference may be due to a reduced mutation rate or to limited tolerance of the large coronavirus genome to incorporate mutations and deletions and remain functional or a combination of both influences. The presence of clade-discordant residues in the progeny of individual biological sub-clones suggests limitations in the occupation of sequence space by SARS-CoV-2. However, the complex and unique mutant spectra that are rapidly generated from individual genomes suggest an aptness to confront selective constraints.

In depth sequencing of a serially sampled household cohort reveals the within-host dynamics of Omicron SARS-CoV-2 and rare selection of novel spike variants

SARS-CoV-2 has undergone repeated and rapid evolution to circumvent host immunity. However, outside of prolonged infections in immunocompromised hosts, within-host positive selection has rarely been detected. Here we combine daily longitudinal sampling of individuals with replicate sequencing to increase the accuracy of and lower the threshold for variant calling. We sequenced 577 specimens from 105 individuals in a household cohort during the BA.1/BA.2 variant period. Individuals exhibited extremely low viral diversity, and we estimated a low within-host evolutionary rate. Within-host dynamics were dominated by genetic drift and purifying selection. Positive selection was rare but highly concentrated in spike. A Wright Fisher Approximate Bayesian Computational model identified positive selection at 14 loci with 7 in spike, including S:448 and S:339. This detectable immune-mediated selection is unusual in acute respiratory infections and may be caused by the relatively narrow antibody repertoire in individuals during the early Omicron phase of the SARS-CoV-2 pandemic.

Within-Host Fitness and Antigenicity Shift Are Key Factors Influencing the Prevalence of Within-Host Variations in the SARS-CoV-2 S Gene

Within-host evolution plays a critical role in shaping the diversity of SARS-CoV-2. However, understanding the primary factors contributing to the prevalence of intra-host single nucleotide variants (iSNVs) in the viral population remains elusive. Here, we conducted a comprehensive analysis of over 556,000 SARS-CoV-2 sequencing data and prevalence data of different SARS-CoV-2 S protein amino acid mutations to elucidate key factors influencing the prevalence of iSNVs in the SARS-CoV-2 S gene. Within-host diversity analysis revealed the presence of mutational hotspots within the S gene, mainly located in NTD, RBD, TM, and CT domains. Additionally, we generated a single amino acid resolution selection status map of the S protein. We observed a significant variance in within-host fitness among iSNVs in the S protein. The majority of iSNVs exhibited low to no within-host fitness and displayed low alternate allele frequency (AAF), suggesting that they will be eliminated due to the narrow transmission bottleneck of SARS-CoV-2. Notably, iSNVs with moderate AAFs (0.06-0.12) were found to be more prevalent than those with high AAFs. Furthermore, iSNVs with the potential to alter antigenicity were more prevalent. These findings underscore the significance of within-host fitness and antigenicity shift as two key factors influencing the prevalence of iSNVs in the SARS-CoV-2 S gene.

SARS-CoV-2 Omicron subvariant genomic variation associations with immune evasion in Northern California: A retrospective cohort study

BACKGROUND

The possibility of association between SARS-CoV-2 genomic variation and immune evasion is not known among persons with Omicron variant SARS-CoV-2 infection.

METHODS

In a retrospective cohort, using Poisson regression adjusting for sociodemographic variables and month of infection, we examined associations between individual non-lineage defining mutations and SARS-CoV-2 immunity status, defined as a) no prior recorded infection, b) not vaccinated but with at least one prior recorded infection, c) complete primary series vaccination, and/or d) primary series vaccination and ≥1 booster. We identified all non-synonymous single nucleotide polymorphisms (SNPs), insertions and deletions in SARS-CoV-2 genomes with ≥5% allelic frequency and population frequency of ≥5% and ≤95%. We also examined correlations between the presence of SNPs with each other, with subvariants, and over time.

RESULTS

Seventy-nine mutations met inclusion criteria. Among 15,566 persons infected with Omicron SARS-CoV-2, 1,825 (12%) were unvaccinated with no prior recorded infection, 360 (2%) were unvaccinated with a recorded prior infection, 13,381 (86%) had a complete primary series vaccination, and 9,172 (58%) had at least one booster. After examining correlation between SNPs, 79 individual non-lineage defining mutations were organized into 38 groups. After correction for multiple testing, no individual SNPs or SNP groups were significantly associated with immunity status levels.

CONCLUSIONS

Genomic variation identified within SARS-CoV-2 Omicron specimens was not significantly associated with immunity status, suggesting that contribution of non-lineage defining SNPs to immune evasion is minimal. Larger-scale surveillance of SARS-CoV-2 genomes linked with clinical data can help provide information to inform future vaccine development.

A general and biomedical perspective of viral quasispecies

Viral quasispecies refers to the complex and dynamic mutant distributions (also termed mutant spectra, clouds, or swarms) that arise as a result of high error rates during RNA genome replication. The mutant spectrum of individual RNA virus populations is modified by continuous generation of variant genomes, competition and interactions among them, environmental influences, bottleneck events, and bloc transmission of viral particles. Quasispecies dynamics provides a new perspective on how viruses adapt, evolve, and cause disease, and sheds light on strategies to combat them. Molecular flexibility, together with ample opportunity of mutant cloud traffic in our global world, are key ingredients of viral disease emergences, as exemplified by the recent COVID-19 pandemic. In the present article, we present a brief overview of the molecular basis of mutant swarm formation and dynamics, and how the latter relates to viral disease and epidemic spread. We outline future challenges derived of the highly diverse cellular world in which viruses are necessarily installed.

Within-host genetic diversity of SARS-CoV-2 across animal species

Infectious disease transmission to different host species makes eradication very challenging and expands the diversity of evolutionary trajectories taken by the pathogen. Since the beginning of the ongoing COVID-19 pandemic, SARS-CoV-2 has been transmitted from humans to many different animal species, in which viral variants of concern could potentially evolve. Previously, using available whole genome consensus sequences of SARS-CoV-2 from four commonly sampled animals (mink, deer, cat, and dog), we inferred similar numbers of transmission events from humans to each animal species. Using a genome-wide association study, we identified 26 single nucleotide variants (SNVs) that tend to occur in deer-more than any other animal-suggesting a high rate of viral adaptation to deer. The reasons for this rapid adaptive evolution remain unclear, but within-host evolution-the ultimate source of the viral diversity that transmits globally-could provide clues. Here, we quantify intra-host SARS-CoV-2 genetic diversity across animal species and show that deer harbor more intra-host SNVs (iSNVs) than other animals, providing a larger pool of genetic diversity for natural selection to act upon. Mixed infections involving more than one viral lineage are unlikely to explain the higher diversity within deer. Rather, a combination of higher mutation rates, longer infections, and species-specific selective pressures are likely explanations. Combined with extensive deer-to-deer transmission, the high levels of within-deer viral diversity help explain the apparent rapid adaptation of SARS-CoV-2 to deer.

Long-term chronic infection of a young immunocompromised patient by the SARS-CoV-2 P.2 VOI

An immunocompromised patient was infected by the SARS-CoV-2 variant of interest named Zeta (P.2) in February 2021. More than one year later, he suffered from symptomatic COVID-19 and sequencing revealed the same variant, which accumulated 23 substitutions. This case illustrates intra-host evolution of a particular SARS-CoV-2 variant, highlighting the importance of genomic surveillance of immunocompromised patients.

Multi-Organ Spread and Intra-Host Diversity of SARS-CoV-2 Support Viral Persistence, Adaptation, and a Mechanism That Increases Evolvability

Intra-host diversity is an intricate phenomenon related to immune evasion, antiviral resistance, and evolutionary leaps along transmission chains. SARS-CoV-2 intra-host variation has been well-evidenced from respiratory samples. However, data on systemic dissemination and diversification are relatively scarce and come from immunologically impaired patients. Here, the presence and variability of SARS-CoV-2 were assessed among 71 tissue samples obtained from multiple organs including lung, intestine, heart, kidney, and liver from 15 autopsies with positive swabs and no records of immunocompromise. The virus was detected in most organs in the majority of autopsies. All organs presented intra-host single nucleotide variants (iSNVs) with low, moderate, and high abundances. The iSNV abundances observed within different organs indicate that the virus can mutate at one host site and subsequently spread to other parts of the body. In agreement with previous data from respiratory samples, our lung samples presented no more than 10 iSNVs each. But interestingly, when analyzing different organs we were able to detect between 11 and 45 iSNVs per case. Our results indicate that SARS-CoV-2 can replicate, and evolve in a compartmentalized manner, in different body sites, which agrees with the "viral reservoir" theory. We elaborate on how compartmentalized evolution in multiple organs may contribute to SARS-CoV-2 evolving so rapidly despite the virus having a proofreading mechanism.

In depth sequencing of a serially sampled household cohort reveals the within-host dynamics of Omicron SARS-CoV-2 and rare selection of novel spike variants

SARS-CoV-2 has undergone repeated and rapid evolution to circumvent host immunity. However, outside of prolonged infections in immunocompromised hosts, within-host positive selection has rarely been detected. The low diversity within-hosts and strong genetic linkage among genomic sites make accurately detecting positive selection difficult. Longitudinal sampling is a powerful method for detecting selection that has seldom been used for SARS-CoV-2. Here we combine longitudinal sampling with replicate sequencing to increase the accuracy of and lower the threshold for variant calling. We sequenced 577 specimens from 105 individuals from a household cohort primarily during the BA.1/BA.2 variant period. There was extremely low diversity and a low rate of divergence. Specimens had 0-12 intrahost single nucleotide variants (iSNV) at >0.5% frequency, and the majority of the iSNV were at frequencies <2%. Within-host dynamics were dominated by genetic drift and purifying selection. Positive selection was rare but highly concentrated in spike. Two individuals with BA.1 infections had S:371F, a lineage defining substitution for BA.2. A Wright Fisher Approximate Bayesian Computational model identified positive selection at 14 loci with 7 in spike, including S:448 and S:339. We also detected significant genetic hitchhiking between synonymous changes and nonsynonymous iSNV under selection. The detectable immune-mediated selection may be caused by the relatively narrow antibody repertoire in individuals during the early Omicron phase of the SARS-CoV-2 pandemic. As both the virus and population immunity evolve, understanding the corresponding shifts in SARS-CoV-2 within-host dynamics will be important.

Random-Effects Substitution Models for Phylogenetics via Scalable Gradient Approximations

Phylogenetic and discrete-trait evolutionary inference depend heavily on an appropriate characterization of the underlying character substitution process. In this paper, we present random-effects substitution models that extend common continuous-time Markov chain models into a richer class of processes capable of capturing a wider variety of substitution dynamics. As these random-effects substitution models often require many more parameters than their usual counterparts, inference can be both statistically and computationally challenging. Thus, we also propose an efficient approach to compute an approximation to the gradient of the data likelihood with respect to all unknown substitution model parameters. We demonstrate that this approximate gradient enables scaling of sampling-based inference, namely Bayesian inference via Hamiltonian Monte Carlo, under random-effects substitution models across large trees and state-spaces. Applied to a dataset of 583 SARS-CoV-2 sequences, an HKY model with random-effects shows strong signals of nonreversibility in the substitution process, and posterior predictive model checks clearly show that it is a more adequate model than a reversible model. When analyzing the pattern of phylogeographic spread of 1441 influenza A virus (H3N2) sequences between 14 regions, a random-effects phylogeographic substitution model infers that air travel volume adequately predicts almost all dispersal rates. A random-effects state-dependent substitution model reveals no evidence for an effect of arboreality on the swimming mode in the tree frog subfamily Hylinae. Simulations reveal that random-effects substitution models can accommodate both negligible and radical departures from the underlying base substitution model. We show that our gradient-based inference approach is over an order of magnitude more time efficient than conventional approaches.

Refining SARS-CoV-2 intra-host variation by leveraging large-scale sequencing data

Understanding viral genome evolution during host infection is crucial for grasping viral diversity and evolution. Analyzing intra-host single nucleotide variants (iSNVs) offers insights into new lineage emergence, which is important for predicting and mitigating future viral threats. Despite next-generation sequencing's potential, challenges persist, notably sequencing artifacts leading to false iSNVs. We developed a workflow to enhance iSNV detection in large NGS libraries, using over 130 000 SARS-CoV-2 libraries to distinguish mutations from errors. Our approach integrates bioinformatics protocols, stringent quality control, and dimensionality reduction to tackle batch effects and improve mutation detection reliability. Additionally, we pioneer the application of the PHATE visualization approach to genomic data and introduce a methodology that quantifies how related groups of data points are represented within a two-dimensional space, enhancing clustering structure explanation based on genetic similarities. This workflow advances accurate intra-host mutation detection, facilitating a deeper understanding of viral diversity and evolution.

Intrahost evolution leading to distinct lineages in the upper and lower respiratory tracts during SARS-CoV-2 prolonged infection

Accumulating evidence points to persistent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in immunocompromised individuals as a source of novel lineages. While intrahost evolution of the virus in chronically infected patients has previously been reported, existing knowledge is primarily based on samples from the nasopharynx. In this study, we investigate the intrahost evolution and genetic diversity that accumulated during a prolonged SARS-CoV-2 infection with the Omicron BF.7 sublineage, which is estimated to have persisted for >1 year in an immunosuppressed patient. Based on the sequencing of eight samples collected at six time points, we identified 87 intrahost single-nucleotide variants, 2 indels, and a 362-bp deletion. Our analysis revealed distinct viral genotypes in the nasopharyngeal (NP), endotracheal aspirate, and bronchoalveolar lavage samples. This suggests that NP samples may not offer a comprehensive representation of the overall intrahost viral diversity. Our findings not only demonstrate that the Omicron BF.7 sublineage can further diverge from its already exceptionally mutated state but also highlight that patients chronically infected with SARS-CoV-2 can develop genetically specific viral populations across distinct anatomic compartments. This provides novel insights into the intricate nature of viral diversity and evolution dynamics in persistent infections.

Comprehensive contact tracing during an outbreak of alpha-variant SARS-CoV-2 in a rural community reveals less viral genomic diversity and higher household secondary attack rates than expected

Sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes throughout the COVID-19 pandemic has generated a wealth of data on viral evolution across populations, but only a few studies have so far explored SARS-CoV-2 evolution across large connected transmission networks. Here, we couple data from SARS-CoV-2 sequencing with contact tracing data from an outbreak with a single origin in a rural Norwegian community where samples from all exposed persons were collected prospectively. A total of 134 nasopharyngeal samples were positive by PCR. Among the 121 retrievable genomes, 81 were identical to the genome of the introductor, thus demonstrating that genomics beyond clustering genotypically similar viral genomes to confirm relatedness offers limited additional value to manual contact tracing. In the cases where mutations were discovered, five small genetic clusters were identified. We observed a household secondary attack rate of 77%, with 92% of household members infected among households with secondary transmission, suggesting that SARS-CoV-2 introduction into large families is likely to affect all household members.

IMPORTANCE

In outbreak investigations, obtaining a full overview of infected individuals within a population is seldom achieved. We here present an example where a single introduction of B1.1.7 SARS-CoV-2 within a rural community allowed for tracing of the virus from an introductor via dissemination through larger gatherings into households. The outbreak occurred before widespread vaccination, allowing for a "natural" outbreak development with community lockdown. We show through sequencing that the virus can infect up to five consecutive persons without gaining mutations, thereby showing that contact tracing seems more important than sequencing for local outbreak investigations in settings with few alternative introductory transmission pathways. We also show how larger households where a child introduced transmission appeared more likely to promote further spread of the virus compared to households with an adult as the primary introductor.

CD4+ and CD8+ T cells are required to prevent SARS-CoV-2 persistence in the nasal compartment

SARS-CoV-2 infection induces the generation of virus-specific CD4+ and CD8+ effector and memory T cells. However, the contribution of T cells in controlling SARS-CoV-2 during infection is not well understood. Following infection of C57BL/6 mice, SARS-CoV-2-specific CD4+ and CD8+ T cells are recruited to the respiratory tract, and a vast proportion secrete the cytotoxic molecule granzyme B. Using depleting antibodies, we found that T cells within the lungs play a minimal role in viral control, and viral clearance occurs in the absence of both CD4+ and CD8+ T cells through 28 days postinfection. In the nasal compartment, depletion of both CD4+ and CD8+ T cells, but not individually, results in persistent, culturable virus replicating in the nasal epithelial layer through 28 days postinfection. Viral sequencing analysis revealed adapted mutations across the SARS-CoV-2 genome, including a large deletion in ORF6. Overall, our findings highlight the importance of T cells in controlling virus replication within the respiratory tract during SARS-CoV-2 infection.

SARS-CoV-2 Omicron subvariant genomic variation associations with immune evasion in Northern California: A retrospective cohort study

Background

The possibility of association between SARS-CoV-2 genomic variation and immune evasion is not known among persons with Omicron variant SARS-CoV-2 infection.

Methods

In a retrospective cohort, using Poisson regression adjusting for sociodemographic variables and month of infection, we examined associations between individual non-lineage defining mutations and SARS-CoV-2 immunity status, defined as a) no prior recorded infection, b) not vaccinated but with at least one prior recorded infection, c) complete primary series vaccination, and/or d) primary series vaccination and ≥ 1 booster. We identified all non-synonymous single nucleotide polymorphisms (SNPs), insertions and deletions in SARS-CoV-2 genomes with ≥5% allelic frequency and population frequency of ≥5% and ≤95%. We also examined correlations between the presence of SNPs with each other, with subvariants, and over time.

Results

Seventy-nine mutations met inclusion criteria. Among 15,566 persons infected with Omicron SARS-CoV-2, 1,825 (12%) were unvaccinated with no prior recorded infection, 360 (2%) were unvaccinated with a recorded prior infection, 13,381 (86%) had a complete primary series vaccination, and 9,172 (58%) had at least one booster. After examining correlation between SNPs, 79 individual non-lineage defining mutations were organized into 38 groups. After correction for multiple testing, no individual SNPs or SNP groups were significantly associated with immunity status levels.

Conclusions

Genomic variation identified within SARS-CoV-2 Omicron specimens was not significantly associated with immunity status, suggesting that contribution of non-lineage defining SNPs to immune evasion is minimal. Larger-scale surveillance of SARS-CoV-2 genomes linked with clinical data can help provide information to inform future vaccine development.

The nuts and bolts of recombination in the generation of SARS-CoV-2 variants; from XA to XBB

Since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), new variants with enhanced transmissibility and pathogenicity have surfaced. The World Health Organization has designated five such variants-Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (B.1.1.529)-as variants of concern. Each variant exhibits distinct characteristics, with many displaying a combination of point mutations and insertions/deletions (indels). These genetic alterations, including mutations, recombinations, and rearrangements, contribute to the emergence of new strains that may exhibit modified phenotypes. However, identifying recombinant forms can be challenging due to their resemblance to other lineages. It is critical to monitor the evolution of new recombinant variants, particularly in light of the potential for vaccine-resistant strains and their accelerated propagation. Recombination has played a pivotal role in the development of certain SARS-CoV-2 variants, such as XA, XD, XF, XE, and XBB, among others. This report delves into the significance of recombination in the evolution of SARS-CoV-2 variants, especially Omicron sublineages, underscoring the necessity for continuous surveillance of the SARS-CoV-2 genome to identify newly emerged recombinant variants.

Difference in TMPRSS2 usage by Delta and Omicron variants of SARS-CoV-2: Implication for a sudden increase among children

It has been postulated from a combination of evidence that a sudden increase in COVID-19 cases among pediatric patients after onset of the Omicron wave was attributed to a reduced requirement for TMPRSS2-mediated entry in pediatric airways with lower expression levels of TMPRSS2. Epidemic strains were isolated from the indigenous population in an area, and the levels of TMPRSS2 required for Delta and Omicron variants were assessed. As a result, Delta variants proliferated fully in cultures of TMPRSS2-positive Vero cells but not in TMPRSS2-negative Vero cell culture (350-fold, Delta vs 9.6-fold, Omicron). There was no obvious age-dependent selection of Omicron strains affected by the TMPRSS2 (9.6-fold, Adults vs. 12-fold, Children). A phylogenetic tree was generated and Blast searches (up to 100 references) for the spread of strains in the study area showed that each strain had almost identical homology (>99.5%) with foreign isolates, although indigenous strains had obvious differences from each other. This suggested that the differences had been present abroad for a long period. Therefore, the lower requirement for TMPRSS2 by Omicron strains might be applicable to epidemic strains globally. In conclusion, the property of TMPRSS2-independent cleavage makes Omicron proliferate with ease and allows epidemics among children with fewer TMPRSS2 on epithelial surfaces of the respiratory organs.

Enforcing Temporal Consistency in Migration History Inference

In addition to undergoing evolution, members of biological populations may also migrate between locations. Examples include the spread of tumor cells from the primary tumor to distant metastases or the spread of pathogens from one host to another. One may represent migration histories by assigning a location label to each vertex of a given phylogenetic tree such that an edge connecting vertices with distinct locations represents a migration. Some biological populations undergo comigration, a phenomenon where multiple taxa from distinct lineages simultaneously comigrate from one location to another. In this work, we show that a previous problem statement for inferring migration histories that are parsimonious in terms of migrations and comigrations may lead to temporally inconsistent solutions. To remedy this deficiency, we introduce precise definitions of temporal consistency of comigrations in a phylogenetic tree, leading to three successive problems. First, we formulate the temporally consistent comigration problem to check if a set of comigrations is temporally consistent and provide a linear time algorithm for solving this problem. Second, we formulate the parsimonious consistent comigrations (PCC) problem, which aims to find comigrations given a location labeling of a phylogenetic tree. We show that PCC is NP-hard. Third, we formulate the parsimonious consistent comigration history (PCCH) problem, which infers the migration history given a phylogenetic tree and locations of its extant vertices only. We show that PCCH is NP-hard as well. On the positive side, we propose integer linear programming models to solve the PCC and PCCH problems. We demonstrate our algorithms on simulated and real data.

Modelling transmission dynamics and genomic diversity in a recombining parasite population

The genomic diversity of a parasite population is shaped by its transmission dynamics but superinfection, cotranmission and recombination make this relationship complex and hard to analyse. This paper aims to simplify the problem by introducing the concept of a genomic transmission graph with three basic parameters: the effective number of hosts, the quantum of transmission and the crossing rate of transmission chains. This enables rapid simulation of coalescence times in a recombining parasite population with superinfection and cotransmission, and it also provides a mathematical framework for analysis of within-host variation. Taking malaria as an example, we use this theoretical model to examine how transmission dynamics and migration affect parasite genomic diversity, including the effective recombination rate and haplotypic metrics of recent common ancestry. We show how key transmission parameters can be inferred from deep sequencing data and as a proof of concept we estimate the Plasmodium falciparum transmission bottleneck. Finally we discuss the potential applications of this novel inferential framework in genomic surveillance for malaria control and elimination. Online tools for exploring the genomic transmission graph are available at d-kwiat.github.io/gtg.

Genomic Diversity and Recombination Analysis of the Spike Protein Gene from Selected Human Coronaviruses

Human coronaviruses (HCoVs) are seriously associated with respiratory diseases in humans and animals. The first human pathogenic SARS-CoV emerged in 2002-2003. The second was MERS-CoV, reported from Jeddah, the Kingdom of Saudi Arabia, in 2012, and the third one was SARS-CoV-2, identified from Wuhan City, China, in late December 2019. The HCoV-Spike (S) gene has the highest mutation/insertion/deletion rate and has been the most utilized target for vaccine/antiviral development. In this manuscript, we discuss the genetic diversity, phylogenetic relationships, and recombination patterns of selected HCoVs with emphasis on the S protein gene of MERS-CoV and SARS-CoV-2 to elucidate the possible emergence of new variants/strains of coronavirus in the near future. The findings showed that MERS-CoV and SARS-CoV-2 have significant sequence identity with the selected HCoVs. The phylogenetic tree analysis formed a separate cluster for each HCoV. The recombination pattern analysis showed that the HCoV-NL63-Japan was a probable recombinant. The HCoV-NL63-USA was identified as a major parent while the HCoV-NL63-Netherland was identified as a minor parent. The recombination breakpoints start in the viral genome at the 142 nucleotide position and end at the 1082 nucleotide position with a 99% CI and Bonferroni-corrected p-value of 0.05. The findings of this study provide insightful information about HCoV-S gene diversity, recombination, and evolutionary patterns. Based on these data, it can be concluded that the possible emergence of new strains/variants of HCoV is imminent.

Sequence signatures within the genome of SARS-CoV-2 can be used to predict host source

We conducted an in silico analysis to better understand the potential factors impacting host adaptation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in white-tailed deer, humans, and mink due to the strong evidence of sustained transmission within these hosts. Classification models trained on single nucleotide and amino acid differences between samples effectively identified white-tailed deer-, human-, and mink-derived SARS-CoV-2. For example, the balanced accuracy score of Extremely Randomized Trees classifiers was 0.984 ± 0.006. Eighty-eight commonly identified predictive mutations are found at sites under strong positive and negative selective pressure. A large fraction of sites under selection (86.9%) or identified by machine learning (87.1%) are found in genes other than the spike. Some locations encoded by these gene regions are predicted to be B- and T-cell epitopes or are implicated in modulating the immune response suggesting that host adaptation may involve the evasion of the host immune system, modulation of the class-I major-histocompatibility complex, and the diminished recognition of immune epitopes by CD8+ T cells. Our selection and machine learning analysis also identified that silent mutations, such as C7303T and C9430T, play an important role in discriminating deer-derived samples across multiple clades. Finally, our investigation into the origin of the B.1.641 lineage from white-tailed deer in Canada discovered an additional human sequence from Michigan related to the B.1.641 lineage sampled near the emergence of this lineage. These findings demonstrate that machine-learning approaches can be used in combination with evolutionary genomics to identify factors possibly involved in the cross-species transmission of viruses and the emergence of novel viral lineages.IMPORTANCESevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible virus capable of infecting and establishing itself in human and wildlife populations, such as white-tailed deer. This fact highlights the importance of developing novel ways to identify genetic factors that contribute to its spread and adaptation to new host species. This is especially important since these populations can serve as reservoirs that potentially facilitate the re-introduction of new variants into human populations. In this study, we apply machine learning and phylogenetic methods to uncover biomarkers of SARS-CoV-2 adaptation in mink and white-tailed deer. We find evidence demonstrating that both non-synonymous and silent mutations can be used to differentiate animal-derived sequences from human-derived ones and each other. This evidence also suggests that host adaptation involves the evasion of the immune system and the suppression of antigen presentation. Finally, the methods developed here are general and can be used to investigate host adaptation in viruses other than SARS-CoV-2.

Enhancing Clinical Utility: Utilization of International Standards and Guidelines for Metagenomic Sequencing in Infectious Disease Diagnosis

Metagenomic sequencing has emerged as a transformative tool in infectious disease diagnosis, offering a comprehensive and unbiased approach to pathogen detection. Leveraging international standards and guidelines is essential for ensuring the quality and reliability of metagenomic sequencing in clinical practice. This review explores the implications of international standards and guidelines for the application of metagenomic sequencing in infectious disease diagnosis. By adhering to established standards, such as those outlined by regulatory bodies and expert consensus, healthcare providers can enhance the accuracy and clinical utility of metagenomic sequencing. The integration of international standards and guidelines into metagenomic sequencing workflows can streamline diagnostic processes, improve pathogen identification, and optimize patient care. Strategies in implementing these standards for infectious disease diagnosis using metagenomic sequencing are discussed, highlighting the importance of standardized approaches in advancing precision infectious disease diagnosis initiatives.

SARS-CoV-2 evolution during prolonged infection in immunocompromised patients

Prolonged infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in immunocompromised patients provides an opportunity for viral evolution, potentially leading to the generation of new pathogenic variants. To investigate the pathways of viral evolution, we carried out a study on five patients experiencing prolonged SARS-CoV-2 infection (quantitative polymerase chain reaction-positive for 79-203 days) who were immunocompromised due to treatment for lymphoma or solid organ transplantation. For each timepoint analyzed, we generated at least two independent viral genome sequences to assess the heterogeneity and control for sequencing error. Four of the five patients likely had prolonged infection; the fifth apparently experienced a reinfection. The rates of accumulation of substitutions in the viral genome per day were higher in hospitalized patients with prolonged infection than those estimated for the community background. The spike coding region accumulated a significantly greater number of unique mutations than other viral coding regions, and the mutation density was higher. Two patients were treated with monoclonal antibodies (bebtelovimab and sotrovimab); by the next sampled timepoint, each virus population showed substitutions associated with monoclonal antibody resistance as the dominant forms (spike K444N and spike E340D). All patients received remdesivir, but remdesivir-resistant substitutions were not detected. These data thus help elucidate the trends of emergence, evolution, and selection of mutational variants within long-term infected immunocompromised individuals.

IMPORTANCE

SARS-CoV-2 is responsible for a global pandemic, driven in part by the emergence of new viral variants. Where do these new variants come from? One model is that long-term viral persistence in infected individuals allows for viral evolution in response to host pressures, resulting in viruses more likely to replicate efficiently in humans. In this study, we characterize replication in several hospitalized and long-term infected individuals, documenting efficient pathways of viral evolution.

Viral genome sequencing to decipher in-hospital SARS-CoV-2 transmission events

The SARS-CoV-2 pandemic has highlighted the need to better define in-hospital transmissions, a need that extends to all other common infectious diseases encountered in clinical settings. To evaluate how whole viral genome sequencing can contribute to deciphering nosocomial SARS-CoV-2 transmission 926 SARS-CoV-2 viral genomes from 622 staff members and patients were collected between February 2020 and January 2021 at a university hospital in Munich, Germany, and analysed along with the place of work, duration of hospital stay, and ward transfers. Bioinformatically defined transmission clusters inferred from viral genome sequencing were compared to those inferred from interview-based contact tracing. An additional dataset collected at the same time at another university hospital in the same city was used to account for multiple independent introductions. Clustering analysis of 619 viral genomes generated 19 clusters ranging from 3 to 31 individuals. Sequencing-based transmission clusters showed little overlap with those based on contact tracing data. The viral genomes were significantly more closely related to each other than comparable genomes collected simultaneously at other hospitals in the same city (n = 829), suggesting nosocomial transmission. Longitudinal sampling from individual patients suggested possible cross-infection events during the hospital stay in 19.2% of individuals (14 of 73 individuals). Clustering analysis of SARS-CoV-2 whole genome sequences can reveal cryptic transmission events missed by classical, interview-based contact tracing, helping to decipher in-hospital transmissions. These results, in line with other studies, advocate for viral genome sequencing as a pathogen transmission surveillance tool in hospitals.

PySNV for complex intra-host variation detection

MOTIVATION

Intra-host variants refer to genetic variations or mutations that occur within an individual host organism. These variants are typically studied in the context of viruses, bacteria, or other pathogens to understand the evolution of pathogens. Moreover, intra-host variants are also explored in the field of tumor biology and mitochondrial biology to characterize somatic mutations and inherited heteroplasmic mutations. Intra-host variants can involve long insertions, deletions, and combinations of different mutation types, which poses challenges in their identification. The performance of current methods in detecting of complex intra-host variants is unknown.

RESULTS

First, we simulated a dataset comprising 10 samples with 1869 intra-host variants involving various mutation patterns and benchmarked current variant detection software. The results indicated that though current software can detect most variants with F1-scores between 0.76 and 0.97, their performance in detecting long indels and low frequency variants was limited. Thus, we developed a new software, PySNV, for the detection of complex intra-host variations. On the simulated dataset, PySNV successfully detected 1863 variant cases (F1-score: 0.99) and exhibited the highest Pearson correlation coefficient (PCC: 0.99) to the ground truth in predicting variant frequencies. The results demonstrated that PySNV delivered promising performance even for long indels and low frequency variants, while maintaining computational speed comparable to other methods. Finally, we tested its performance on SARS-CoV-2 replicate sequencing data and found that it reported 21% more variants compared to LoFreq, the best-performing benchmarked software, while showing higher consistency (62% over 54%) within replicates. The discrepancies mostly exist in low-depth regions and low frequency variants.

AVAILABILITY AND IMPLEMENTATION

https://github.com/bnuLyndon/PySNV/.

SARS-CoV-2 rapidly evolves lineage-specific phenotypic differences when passaged repeatedly in immune-naïve mice

The persistence of SARS-CoV-2 despite the development of vaccines and a degree of herd immunity is partly due to viral evolution reducing vaccine and treatment efficacy. Serial infections of wild-type (WT) SARS-CoV-2 in Balb/c mice yield mouse-adapted strains with greater infectivity and mortality. We investigate if passaging unmodified B.1.351 (Beta) and B.1.617.2 (Delta) 20 times in K18-ACE2 mice, expressing the human ACE2 receptor, in a BSL-3 laboratory without selective pressures, drives human health-relevant evolution and if evolution is lineage-dependent. Late-passage virus causes more severe disease, at organism and lung tissue scales, with late-passage Delta demonstrating antibody resistance and interferon suppression. This resistance co-occurs with a de novo spike S371F mutation, linked with both traits. S371F, an Omicron-characteristic mutation, is co-inherited at times with spike E1182G per Nanopore sequencing, existing in different within-sample viral variants at others. Both S371F and E1182G are linked to mammalian GOLGA7 and ZDHHC5 interactions, which mediate viral-cell entry and antiviral response. This study demonstrates SARS-CoV-2's tendency to evolve with phenotypic consequences, its evolution varying by lineage, and suggests non-dominant quasi-species contribution.

Extreme infectious titer variability in individual Aedes aegypti mosquitoes infected with Sindbis virus is associated with both differences in virus population structure and dramatic disparities in specific infectivity

Variability in how individuals respond to pathogens is a hallmark of infectious disease, yet the basis for individual variation in host response is often poorly understood. The titer of infectious virus among individual mosquitoes infected with arboviruses is frequently observed to vary by several orders of magnitude in a single experiment, even when the mosquitoes are highly inbred. To better understand the basis for this titer variation, we sequenced populations of Sindbis virus (SINV) obtained from individual infected Aedes aegypti mosquitoes that, despite being from a highly inbred laboratory colony, differed in their titers of infectious virus by approximately 10,000-fold. We observed genetic differences between these virus populations that indicated the virus present in the midguts of low titer mosquitoes was less fit than that of high titer mosquitoes, possibly due to founder effects that occurred during midgut infection. Furthermore, we found dramatic differences in the specific infectivity or SI (the ratio of infectious units/viral genome equivalents) between these virus populations, with the SI of low titer mosquitoes being up to 10,000-fold lower than that of high titer mosquitoes. Despite having similar amounts of viral genomes, low titer mosquitoes appeared to contain less viral particles, suggesting that viral genomes were packaged into virions less efficiently than in high titer mosquitoes. Finally, antibiotic treatment, which has been shown to suppress mosquito antiviral immunity, caused an increase in SI. Our results indicate that the extreme variation that is observed in SINV infectious titer between individual Ae. aegypti mosquitoes is due to both genetic differences between virus populations and to differences in the proportion of genomes that are packaged into infectious particles.

CD4+ and CD8+ T cells are required to prevent SARS-CoV-2 persistence in the nasal compartment

SARS-CoV-2 is the causative agent of COVID-19 and continues to pose a significant public health threat throughout the world. Following SARS-CoV-2 infection, virus-specific CD4+ and CD8+ T cells are rapidly generated to form effector and memory cells and persist in the blood for several months. However, the contribution of T cells in controlling SARS-CoV-2 infection within the respiratory tract are not well understood. Using C57BL/6 mice infected with a naturally occurring SARS-CoV-2 variant (B.1.351), we evaluated the role of T cells in the upper and lower respiratory tract. Following infection, SARS-CoV-2-specific CD4+ and CD8+ T cells are recruited to the respiratory tract and a vast proportion secrete the cytotoxic molecule Granzyme B. Using antibodies to deplete T cells prior to infection, we found that CD4+ and CD8+ T cells play distinct roles in the upper and lower respiratory tract. In the lungs, T cells play a minimal role in viral control with viral clearance occurring in the absence of both CD4+ and CD8+ T cells through 28 days post-infection. In the nasal compartment, depletion of both CD4+ and CD8+ T cells, but not individually, results in persistent and culturable virus replicating in the nasal compartment through 28 days post-infection. Using in situ hybridization, we found that SARS-CoV-2 infection persisted in the nasal epithelial layer of tandem CD4+ and CD8+ T cell-depleted mice. Sequence analysis of virus isolates from persistently infected mice revealed mutations spanning across the genome, including a deletion in ORF6. Overall, our findings highlight the importance of T cells in controlling virus replication within the respiratory tract during SARS-CoV-2 infection.

Within-host evolutionary dynamics and tissue compartmentalization during acute SARS-CoV-2 infection

The global evolution of SARS-CoV-2 depends in part upon the evolutionary dynamics within individual hosts with varying immune histories. To characterize the within-host evolution of acute SARS-CoV-2 infection, we sequenced saliva and nasal samples collected daily from vaccinated and unvaccinated individuals early during infection. We show that longitudinal sampling facilitates high-confidence genetic variant detection and reveals evolutionary dynamics missed by less-frequent sampling strategies. Within-host dynamics in both unvaccinated and vaccinated individuals appeared largely stochastic; however, in rare cases, minor genetic variants emerged to frequencies sufficient for forward transmission. Finally, we detected significant genetic compartmentalization of viral variants between saliva and nasal swab sample sites in many individuals. Altogether, these data provide a high-resolution profile of within-host SARS-CoV-2 evolutionary dynamics.IMPORTANCEWe detail the within-host evolutionary dynamics of SARS-CoV-2 during acute infection in 31 individuals using daily longitudinal sampling. We characterized patterns of mutational accumulation for unvaccinated and vaccinated individuals, and observed that temporal variant dynamics in both groups were largely stochastic. Comparison of paired nasal and saliva samples also revealed significant genetic compartmentalization between tissue environments in multiple individuals. Our results demonstrate how selection, genetic drift, and spatial compartmentalization all play important roles in shaping the within-host evolution of SARS-CoV-2 populations during acute infection.

Genomic surveillance reveals dynamic shifts in the connectivity of COVID-19 epidemics

The maturation of genomic surveillance in the past decade has enabled tracking of the emergence and spread of epidemics at an unprecedented level. During the COVID-19 pandemic, for example, genomic data revealed that local epidemics varied considerably in the frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage importation and persistence, likely due to a combination of COVID-19 restrictions and changing connectivity. Here, we show that local COVID-19 epidemics are driven by regional transmission, including across international boundaries, but can become increasingly connected to distant locations following the relaxation of public health interventions. By integrating genomic, mobility, and epidemiological data, we find abundant transmission occurring between both adjacent and distant locations, supported by dynamic mobility patterns. We find that changing connectivity significantly influences local COVID-19 incidence. Our findings demonstrate a complex meaning of "local" when investigating connected epidemics and emphasize the importance of collaborative interventions for pandemic prevention and mitigation.

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.

Severe Acute Respiratory Syndrome Coronavirus 2 Delta Variant Genomic Variation Associated With Breakthrough Infection in Northern California: A Retrospective Cohort Study

BACKGROUND

The association between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic variation and breakthrough infection is not well defined among persons with Delta variant SARS-CoV-2 infection.

METHODS

In a retrospective cohort, we assessed whether individual nonlineage defining mutations and overall genomic variation (including low-frequency alleles) were associated with breakthrough infection, defined as SARS-CoV-2 infection after coronavirus disease 2019 primary vaccine series. We identified all nonsynonymous single-nucleotide polymorphisms, insertions, and deletions in SARS-CoV-2 genomes with ≥5% allelic frequency and population frequency of ≥5% and ≤95%. Using Poisson regression, we assessed the association with breakthrough infection for each individual mutation and a viral genomic risk score.

RESULTS

Thirty-six mutations met our inclusion criteria. Among 12 744 persons infected with Delta variant SARS-CoV-2, 5949 (47%) were vaccinated and 6795 (53%) were unvaccinated. Viruses with a viral genomic risk score in the highest quintile were 9% more likely to be associated with breakthrough infection than viruses in the lowest quintile, but including the risk score improved overall predictive model performance (measured by C statistic) by only +0.0006.

CONCLUSIONS

Genomic variation within SARS-CoV-2 Delta variant was weakly associated with breakthrough infection, but several potential nonlineage defining mutations were identified that might contribute to immune evasion by SARS-CoV-2.

Within-host diversity improves phylogenetic and transmission reconstruction of SARS-CoV-2 outbreaks

Accurate inference of who infected whom in an infectious disease outbreak is critical for the delivery of effective infection prevention and control. The increased resolution of pathogen whole-genome sequencing has significantly improved our ability to infer transmission events. Despite this, transmission inference often remains limited by the lack of genomic variation between the source case and infected contacts. Although within-host genetic diversity is common among a wide variety of pathogens, conventional whole-genome sequencing phylogenetic approaches exclusively use consensus sequences, which consider only the most prevalent nucleotide at each position and therefore fail to capture low-frequency variation within samples. We hypothesized that including within-sample variation in a phylogenetic model would help to identify who infected whom in instances in which this was previously impossible. Using whole-genome sequences from SARS-CoV-2 multi-institutional outbreaks as an example, we show how within-sample diversity is partially maintained among repeated serial samples from the same host, it can transmitted between those cases with known epidemiological links, and how this improves phylogenetic inference and our understanding of who infected whom. Our technique is applicable to other infectious diseases and has immediate clinical utility in infection prevention and control.

Investigation of the individual genetic evolution of SARS-CoV-2 in a small cluster during the rapid spread of the BF.5 lineage in Tokyo, Japan

There has been a decreasing trend in new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases and fatalities worldwide. The virus has been evolving, indicating the potential emergence of new variants and uncertainties. These challenges necessitate continued efforts in disease control and mitigation strategies. We investigated a small cluster of SARS-CoV-2 Omicron variant infections containing a common set of genomic mutations, which provided a valuable model for investigating the transmission mechanism of genetic alterations. We conducted a study at a medical center in Japan during the Omicron surge (sub-lineage BA.5), sequencing the entire SARS-CoV-2 genomes from infected individuals and evaluating the phylogenetic tree and haplotype network among the variants. We compared the mutations present in each strain within the BA.5 strain, TKYnat2317, which was first identified in Tokyo, Japan. From June 29th to July 4th 2022, nine healthcare workers (HCWs) tested positive for SARS-CoV-2 by real-time PCR. During the same period, five patients also tested positive by real-time PCR. Whole genome sequencing revealed that the infected patients belonged to either the isolated BA.2 or BA.5 sub-lineage, while the healthcare worker infections were classified as BF.5. The phylogenetic tree and haplotype network clearly showed the specificity and similarity of the HCW cluster. We identified 12 common mutations in the cluster, including I110V in nonstructural protein 4 (nsp4), A1020S in the Spike protein, and H47Y in ORF7a, compared to the BA.5 reference. Additionally, one case had the extra nucleotide-deletion mutation I27* in ORF10, and low frequencies of genetic alterations were also found in certain instances. The results of genome sequencing showed that the nine HCWs shared a set of genetic mutations, indicating transmission within the cluster. Minor mutations observed in five HCW individuals suggested the emergence of new virus variants. Five amino acid substitutions occurred in nsp3, which could potentially affect virus replication or immune escape. Intra-host evolution also generated additional mutations. The cluster exhibited a mild disease course, with individuals in this case, recovering without requiring any medical treatments. Further investigation is needed to understand the relationship between the genetic evolution of the virus and the symptoms.

Clinical outcomes and phylogenetic analysis in reflection with three predominant clades of SARS-CoV-2 variants

BACKGROUND

The pandemic of coronavirus disease 2019 (COVID-19) has a broad spectrum of clinical manifestations. The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) undergoes continuous evolution, resulting in the emergence of several variants. Each variant has a different severity and mortality rate.

MATERIALS AND METHODS

In this study, 1174 COVID-19 patients were studied for mortality and severity over three SARS-CoV-2 predominating variant periods in 2021 and 2022 in Sulaimani Province, Iraq. In each period, a representative, variant virus was subjected to phylogenetic and molecular and clinical analysis.

RESULTS

Phylogenetic analysis revealed three SARS-CoV-2 variants, belonging to: Delta B.1.617.2, Omicron BA.1.17.2, and Omicron BA.5.6. The Delta variants showed more severe symptoms and a lower PCR-Ct value than Omicron variants regardless of gender, and only 4.3% of the cases were asymptomatic. The mortality rate was lower with Omicron (.5% for BA.5.2 and 1.3% for BA.1.17.2) compared with Delta variants (2.5%). The higher mortality rate with Delta variants was in males (2.84%), while that with Omicron BA1.17.2 and BA.5.2 was in females, 1.05% and .0%, respectively. Age group (≥70) years had the highest mortality rate; however, it was (.0%) in the age group (30-49) years with Omicron variants, compared with (.96%) in Delta variants.

CONCLUSIONS

There has been a surge in COVID-19 infection in the city due to the predominant lineages of SARS-CoV-2, B.1.617, Omicron BA.1.17.2 and Omicron BA.5.6, respectively. A higher PCR-Ct value and severity of the Delta variant over Omicron BA.1.17.2 and/or BA.5.2 variants were significantly correlated with a higher death rate in the same order.

Immune evasion and ACE2 binding affinity contribute to SARS-CoV-2 evolution

Mutations in the SARS-CoV-2 genome could confer resistance to pre-existing antibodies and/or increased transmissibility. The recently emerged Omicron subvariants exhibit a strong tendency for immune evasion, suggesting adaptive evolution. However, because previous studies have been limited to specific lineages or subsets of mutations, the overall evolutionary trajectory of SARS-CoV-2 and the underlying driving forces are still not fully understood. Here we analysed all open-access SARS-CoV-2 genomes (up to November 2022) and correlated the mutation incidence and fitness changes with the impacts of mutations on immune evasion and ACE2 binding affinity. Our results show that the Omicron lineage had an accelerated mutation rate in the RBD region, while the mutation incidence in other genomic regions did not change dramatically over time. Mutations in the RBD region exhibited a lineage-specific pattern and tended to become more aggregated over time, and the mutation incidence was positively correlated with the strength of antibody pressure. Additionally, mutation incidence was positively correlated with changes in ACE2 binding affinity, but with a lower correlation coefficient than with immune evasion. In contrast, the effect of mutations on fitness was more closely correlated with changes in ACE2 binding affinity than with immune evasion. Our findings suggest that immune evasion and ACE2 binding affinity play significant and diverse roles in the evolution of SARS-CoV-2.

Optimized quantification of intra-host viral diversity in SARS-CoV-2 and influenza virus sequence data

High error rates of viral RNA-dependent RNA polymerases lead to diverse intra-host viral populations during infection. Errors made during replication that are not strongly deleterious to the virus can lead to the generation of minority variants. However, accurate detection of minority variants in viral sequence data is complicated by errors introduced during sample preparation and data analysis. We used synthetic RNA controls and simulated data to test seven variant-calling tools across a range of allele frequencies and simulated coverages. We show that choice of variant caller and use of replicate sequencing have the most significant impact on single-nucleotide variant (SNV) discovery and demonstrate how both allele frequency and coverage thresholds impact both false discovery and false-negative rates. When replicates are not available, using a combination of multiple callers with more stringent cutoffs is recommended. We use these parameters to find minority variants in sequencing data from SARS-CoV-2 clinical specimens and provide guidance for studies of intra-host viral diversity using either single replicate data or data from technical replicates. Our study provides a framework for rigorous assessment of technical factors that impact SNV identification in viral samples and establishes heuristics that will inform and improve future studies of intra-host variation, viral diversity, and viral evolution. IMPORTANCE When viruses replicate inside a host cell, the virus replication machinery makes mistakes. Over time, these mistakes create mutations that result in a diverse population of viruses inside the host. Mutations that are neither lethal to the virus nor strongly beneficial can lead to minority variants that are minor members of the virus population. However, preparing samples for sequencing can also introduce errors that resemble minority variants, resulting in the inclusion of false-positive data if not filtered correctly. In this study, we aimed to determine the best methods for identification and quantification of these minority variants by testing the performance of seven commonly used variant-calling tools. We used simulated and synthetic data to test their performance against a true set of variants and then used these studies to inform variant identification in data from SARS-CoV-2 clinical specimens. Together, analyses of our data provide extensive guidance for future studies of viral diversity and evolution.

SARS-CoV-2 within-host diversity of human hosts and its implications for viral immune evasion

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is continuously evolving, bringing great challenges to the control of the virus. In the present study, we investigated the characteristics of SARS-CoV-2 within-host diversity of human hosts and its implications for immune evasion using about 2,00,000 high-depth next-generation genome sequencing data of SARS-CoV-2. A total of 44% of the samples showed within-host variations (iSNVs), and the average number of iSNVs in the samples with iSNV was 1.90. C-to-U is the dominant substitution pattern for iSNVs. C-to-U/G-to-A and A-to-G/U-to-C preferentially occur in 5'-CG-3' and 5'-AU-3' motifs, respectively. In addition, we found that SARS-CoV-2 within-host variations are under negative selection. About 15.6% iSNVs had an impact on the content of the CpG dinucleotide (CpG) in SARS-CoV-2 genomes. We detected signatures of faster loss of CpG-gaining iSNVs, possibly resulting from zinc-finger antiviral protein-mediated antiviral activities targeting CpG, which could be the major reason for CpG depletion in SARS-CoV-2 consensus genomes. The non-synonymous iSNVs in the S gene can largely alter the S protein's antigenic features, and many of these iSNVs are distributed in the amino-terminal domain (NTD) and receptor-binding domain (RBD). These results suggest that SARS-CoV-2 interacts actively with human hosts and attempts to take different evolutionary strategies to escape human innate and adaptive immunity. These new findings further deepen and widen our understanding of the within-host evolutionary features of SARS-CoV-2. IMPORTANCE Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pathogen of the coronavirus disease 2019, has evolved rapidly since it was discovered. Recent studies have pointed out that some mutations in the SARS-CoV-2 S protein could confer SARS-CoV-2 the ability to evade the human adaptive immune system. In addition, it is observed that the content of the CpG dinucleotide in SARS-CoV-2 genome sequences has decreased over time, reflecting the adaptation to the human host. The significance of our research is revealing the characteristics of SARS-CoV-2 within-host diversity of human hosts, identifying the causes of CpG depletion in SARS-CoV-2 consensus genomes, and exploring the potential impacts of non-synonymous within-host variations in the S gene on immune escape, which could further deepen and widen our understanding of the evolutionary features of SARS-CoV-2.

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.

Intra- and interhost genomic diversity of monkeypox virus

The impact and frequency of infectious disease outbreaks demonstrate the need for timely genomic surveillance to inform public health responses. In the largest known outbreak of mpox, genomic surveillance efforts have primarily focused on high-incidence nations in Europe and the Americas, with a paucity of data from South-East Asia and the Western Pacific. Here we analyzed 102 monkeypox virus (MPXV) genomes sampled from 56 individuals in Melbourne, Australia. All genomes fell within the 2022 MPXV outbreak lineage (B.1), with likely onward local transmission detected. We observed within-host diversity and instances of co-infection, and highlight further examples of structural variation and apolipoprotein B editing complex-driven micro-evolution in the current MPXV outbreak. Updating our understanding of MPXV emergence and diversification will inform public health measures and enable monitoring of the virus' evolutionary trajectory throughout the mpox outbreak.

Assessing the evolution of SARS-CoV-2 lineages and the dynamic associations between nucleotide variations

Despite seminal advances towards understanding the infection mechanism of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), it continues to cause significant morbidity and mortality worldwide. Though mass immunization programmes have been implemented in several countries, the viral transmission cycle has shown a continuous progression in the form of multiple waves. A constant change in the frequencies of dominant viral lineages, arising from the accumulation of nucleotide variations (NVs) through favourable selection, is understandably expected to be a major determinant of disease severity and possible vaccine escape. Indeed, worldwide efforts have been initiated to identify specific virus lineage(s) and/or NVs that may cause a severe clinical presentation or facilitate vaccination breakthrough. Since host genetics is expected to play a major role in shaping virus evolution, it is imperative to study the role of genome-wide SARS-CoV-2 NVs across various populations. In the current study, we analysed the whole genome sequence of 3543 SARS-CoV-2-infected samples obtained from the state of Telangana, India (including 210 from our previous study), collected over an extended period from April 2020 to October 2021. We present a unique perspective on the evolution of prevalent virus lineages and NVs during this period. We also highlight the presence of specific NVs likely to be associated favourably with samples classified as vaccination breakthroughs. Finally, we report genome-wide intra-host variations at novel genomic positions. The results presented here provide critical insights into virus evolution over an extended period and pave the way to rigorously investigate the role of specific NVs in vaccination breakthroughs.

SARS-CoV-2 entry into and evolution within a skilled nursing facility

SARS-CoV-2 belongs to the family Coronaviridae which includes multiple human pathogens that have an outsized impact on aging populations. As a novel human pathogen, SARS-CoV-2 is undergoing continuous adaptation to this new host species and there is evidence of this throughout the scientific and public literature. However, most investigations of SARS-CoV-2 evolution have focused on large-scale collections of data across diverse populations and/or living environments. Here we investigate SARS-CoV-2 evolution in epidemiologically linked individuals within a single outbreak at a skilled nursing facility beginning with initial introduction of the pathogen. The data demonstrate that SARS-CoV-2 was introduced to the facility multiple times without establishing an interfacility transmission chain, followed by a single introduction that infected many individuals within a week. This large-scale introduction by a single genotype then persisted in the facility. SARS-CoV-2 sequences were investigated at both the consensus and intra-host variation levels. Understanding the variability in SARS-CoV-2 during transmission chains will assist in understanding the spread of this disease and can ultimately inform best practices for mitigation strategies.

Sequential intrahost evolution and onward transmission of SARS-CoV-2 variants

Persistent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections have been reported in immune-compromised individuals and people undergoing immune-modulatory treatments. Although intrahost evolution has been documented, direct evidence of subsequent transmission and continued stepwise adaptation is lacking. Here we describe sequential persistent SARS-CoV-2 infections in three individuals that led to the emergence, forward transmission, and continued evolution of a new Omicron sublineage, BA.1.23, over an eight-month period. The initially transmitted BA.1.23 variant encoded seven additional amino acid substitutions within the spike protein (E96D, R346T, L455W, K458M, A484V, H681R, A688V), and displayed substantial resistance to neutralization by sera from boosted and/or Omicron BA.1-infected study participants. Subsequent continued BA.1.23 replication resulted in additional substitutions in the spike protein (S254F, N448S, F456L, M458K, F981L, S982L) as well as in five other virus proteins. Our findings demonstrate not only that the Omicron BA.1 lineage can diverge further from its already exceptionally mutated genome but also that patients with persistent infections can transmit these viral variants. Thus, there is, an urgent need to implement strategies to prevent prolonged SARS-CoV-2 replication and to limit the spread of newly emerging, neutralization-resistant variants in vulnerable patients.

Traceability of SARS-CoV-2 transmission through quasispecies analysis

During COVID-19 pandemic, consensus genomic sequences were used for rapidly monitor the spread of the virus worldwide. However, less attention was paid to intrahost genetic diversity. In fact, in the infected host, SARS-CoV-2 consists in an ensemble of replicating and closely related viral variants so-called quasispecies. Here we show that intrahost single nucleotide variants (iSNVs) represent a target for contact tracing analysis. Our data indicate that in the acute phase of infection, in highly likely transmission links, the number of viral particles transmitted from one host to another (bottleneck size) is large enough to propagate iSNVs among individuals. Furthermore, we demonstrate that, during SARS-CoV-2 outbreaks when the consensus sequences are identical, it is possible to reconstruct the transmission chains by genomic investigations of iSNVs. Specifically, we found that it is possible to identify transmission chains by limiting the analysis of iSNVs to only three well-conserved genes, namely nsp2, ORF3, and ORF7.

Mutation bias and the predictability of evolution

Predicting evolutionary outcomes is an important research goal in a diversity of contexts. The focus of evolutionary forecasting is usually on adaptive processes, and efforts to improve prediction typically focus on selection. However, adaptive processes often rely on new mutations, which can be strongly influenced by predictable biases in mutation. Here, we provide an overview of existing theory and evidence for such mutation-biased adaptation and consider the implications of these results for the problem of prediction, in regard to topics such as the evolution of infectious diseases, resistance to biochemical agents, as well as cancer and other kinds of somatic evolution. We argue that empirical knowledge of mutational biases is likely to improve in the near future, and that this knowledge is readily applicable to the challenges of short-term prediction. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Modeling identifies variability in SARS-CoV-2 uptake and eclipse phase by infected cells as principal drivers of extreme variability in nasal viral load in the 48 h post infection

The SARS-CoV-2 coronavirus continues to evolve with scores of mutations of the spike, membrane, envelope, and nucleocapsid structural proteins that impact pathogenesis. Infection data from nasal swabs, nasal PCR assays, upper respiratory samples, ex vivo cell cultures and nasal epithelial organoids reveal extreme variabilities in SARS-CoV-2 RNA titers within and between the variants. Some variabilities are naturally prone to clinical testing protocols and experimental controls. Here we focus on nasal viral load sensitivity arising from the timing of sample collection relative to onset of infection and from heterogeneity in the kinetics of cellular infection, uptake, replication, and shedding of viral RNA copies. The sources of between-variant variability are likely due to SARS-CoV-2 structural protein mutations, whereas within-variant population variability is likely due to heterogeneity in cellular response to that particular variant. With the physiologically faithful, agent-based mechanistic model of inhaled exposure and infection from (Chen et al., 2022), we perform statistical sensitivity analyses of the progression of nasal viral titers in the first 0-48 h post infection, focusing on three kinetic mechanisms. Model simulations reveal shorter latency times of infected cells (including cellular uptake, viral RNA replication, until the onset of viral RNA shedding) exponentially accelerate nasal viral load. Further, the rate of infectious RNA copies shed per day has a proportional influence on nasal viral load. Finally, there is a very weak, negative correlation of viral load with the probability of infection per virus-cell encounter, the model proxy for spike-receptor binding affinity.

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.

Developing an appropriate evolutionary baseline model for the study of SARS-CoV-2 patient samples

Over the past 3 years, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has spread through human populations in several waves, resulting in a global health crisis. In response, genomic surveillance efforts have proliferated in the hopes of tracking and anticipating the evolution of this virus, resulting in millions of patient isolates now being available in public databases. Yet, while there is a tremendous focus on identifying newly emerging adaptive viral variants, this quantification is far from trivial. Specifically, multiple co-occurring and interacting evolutionary processes are constantly in operation and must be jointly considered and modeled in order to perform accurate inference. We here outline critical individual components of such an evolutionary baseline model-mutation rates, recombination rates, the distribution of fitness effects, infection dynamics, and compartmentalization-and describe the current state of knowledge pertaining to the related parameters of each in SARS-CoV-2. We close with a series of recommendations for future clinical sampling, model construction, and statistical analysis.