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

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.

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.

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.

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.

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.

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.

Within-host genetic diversity of SARS-CoV-2 lineages in unvaccinated and vaccinated individuals

Viral and host factors can shape SARS-CoV-2 evolution. However, little is known about lineage-specific and vaccination-specific mutations that occur within individuals. Here, we analysed deep sequencing data from 2,820 SARS-CoV-2 respiratory samples with different viral lineages to describe the patterns of within-host diversity under different conditions, including vaccine-breakthrough infections. In unvaccinated individuals, variant of Concern (VOC) Alpha, Delta, and Omicron respiratory samples were found to have higher within-host diversity and were under neutral to purifying selection at the full genome level compared to non-VOC SARS-CoV-2. Breakthrough infections in 2-dose or 3-dose Comirnaty and CoronaVac vaccinated individuals did not increase levels of non-synonymous mutations and did not change the direction of selection pressure. Vaccine-induced antibody or T cell responses did not appear to have significant impact on within-host SARS-CoV-2 sequence diversification. Our findings suggest that vaccination does not increase exploration of SARS-CoV-2 protein sequence space and may not facilitate emergence of viral variants.

Host immunological responses facilitate development of SARS-CoV-2 mutations in patients receiving monoclonal antibody treatments

BackgroundThe role of host immunity in emergence of evasive SARS-CoV-2 Spike mutations under therapeutic monoclonal antibody (mAb) pressure remains to be explored.MethodsIn a prospective, observational, monocentric ORCHESTRA cohort study, conducted between March 2021 and November 2022, mild-to-moderately ill COVID-19 patients (n = 204) receiving bamlanivimab, bamlanivimab/etesevimab, casirivimab/imdevimab, or sotrovimab were longitudinally studied over 28 days for viral loads, de novo Spike mutations, mAb kinetics, seroneutralization against infecting variants of concern, and T cell immunity. Additionally, a machine learning-based circulating immune-related biomarker (CIB) profile predictive of evasive Spike mutations was constructed and confirmed in an independent data set (n = 19) that included patients receiving sotrovimab or tixagevimab/cilgavimab.ResultsPatients treated with various mAbs developed evasive Spike mutations with remarkable speed and high specificity to the targeted mAb-binding sites. Immunocompromised patients receiving mAb therapy not only continued to display significantly higher viral loads, but also showed higher likelihood of developing de novo Spike mutations. Development of escape mutants also strongly correlated with neutralizing capacity of the therapeutic mAbs and T cell immunity, suggesting immune pressure as an important driver of escape mutations. Lastly, we showed that an antiinflammatory and healing-promoting host milieu facilitates Spike mutations, where 4 CIBs identified patients at high risk of developing escape mutations against therapeutic mAbs with high accuracy.ConclusionsOur data demonstrate that host-driven immune and nonimmune responses are essential for development of mutant SARS-CoV-2. These data also support point-of-care decision making in reducing the risk of mAb treatment failure and improving mitigation strategies for possible dissemination of escape SARS-CoV-2 mutants.FundingThe ORCHESTRA project/European Union's Horizon 2020 research and innovation program.

TaME-seq2: tagmentation-assisted multiplex PCR enrichment sequencing for viral genomic profiling

BACKGROUND

Previously developed TaME-seq method for deep sequencing of HPV, allowed simultaneous identification of the human papillomavirus (HPV) DNA consensus sequence, low-frequency variable sites, and chromosomal integration events. The method has been successfully validated and applied to the study of five carcinogenic high-risk (HR) HPV types (HPV16, 18, 31, 33, and 45). Here, we present TaME-seq2 with an updated laboratory workflow and bioinformatics pipeline. The HR-HPV type repertoire was expanded with HPV51, 52, and 59. As a proof-of-concept, TaME-seq2 was applied on SARS-CoV-2 positive samples showing the method's flexibility to a broader range of viruses, both DNA and RNA.

RESULTS

Compared to TaME-seq version 1, the bioinformatics pipeline of TaME-seq2 is approximately 40× faster. In total, 23 HPV-positive samples and seven SARS-CoV-2 clinical samples passed the threshold of 300× mean depth and were submitted to further analysis. The mean number of variable sites per 1 kb was ~ 1.5× higher in SARS-CoV-2 than in HPV-positive samples. Reproducibility and repeatability of the method were tested on a subset of samples. A viral integration breakpoint followed by a partial genomic deletion was found in within-run replicates of HPV59-positive sample. Identified viral consensus sequence in two separate runs was > 99.9% identical between replicates, differing by a couple of nucleotides identified in only one of the replicates. Conversely, the number of identical minor nucleotide variants (MNVs) differed greatly between replicates, probably caused by PCR-introduced bias. The total number of detected MNVs, calculated gene variability and mutational signature analysis, were unaffected by the sequencing run.

CONCLUSION

TaME-seq2 proved well suited for consensus sequence identification, and the detection of low-frequency viral genome variation and viral-chromosomal integrations. The repertoire of TaME-seq2 now encompasses seven HR-HPV types. Our goal is to further include all HR-HPV types in the TaME-seq2 repertoire. Moreover, with a minor modification of previously developed primers, the same method was successfully applied for the analysis of SARS-CoV-2 positive samples, implying the ease of adapting TaME-seq2 to other viruses.

Accelerated SARS-CoV-2 intrahost evolution leading to distinct genotypes during chronic infection

The chronic infection hypothesis for novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant emergence is increasingly gaining credence following the appearance of Omicron. Here, we investigate intrahost evolution and genetic diversity of lineage B.1.517 during a SARS-CoV-2 chronic infection lasting for 471 days (and still ongoing) with consistently recovered infectious virus and high viral genome copies. During the infection, we find an accelerated virus evolutionary rate translating to 35 nucleotide substitutions per year, approximately 2-fold higher than the global SARS-CoV-2 evolutionary rate. This intrahost evolution results in the emergence and persistence of at least three genetically distinct genotypes, suggesting the establishment of spatially structured viral populations continually reseeding different genotypes into the nasopharynx. Finally, we track the temporal dynamics of genetic diversity to identify advantageous mutations and highlight hallmark changes for chronic infection. Our findings demonstrate that untreated chronic infections accelerate SARS-CoV-2 evolution, providing an opportunity for the emergence of genetically divergent variants.

SARS-CoV-2 evolution among patients with immunosuppression in a nosocomial cluster of a Japanese medical center during the Delta (AY.29 sublineage) surge

Background

Previous studies have shown that patients with immunosuppression tend to have longer-lasting SARS-CoV-2 infections and a number of mutations were observed during the infection period. However, these studies were, in general, conducted longitudinally. Mutation evolution among groups of patients with immunosuppression have not been well studied, especially among Asian populations.

Methods

Our study targeted a nosocomial cluster of SARS-CoV-2 infection in a Japanese medical center during Delta surge (AY.29 sublineage), involving ward nurses and inpatients. Whole-genome sequencing analyses were performed to examine mutation changes. Haplotype and minor variant analyses were furtherly performed to detect the mutations on the viral genomes in detail. In addition, sequences of the first wild-type strain hCoV-19/Wuhan/WIV04/2019 and AY.29 wild-type strain hCoV-19/Japan/TKYK15779/2021 were used as references to assess the phylogenetical development of this cluster.

Results

A total of 6 nurses and 14 inpatients were identified as a nosocomial cluster from September 14 through 28, 2021. All were Delta variant (AY.29 sublineage) positive. 92.9% of infected patients (13 out of 14) were either cancer patients and/or receiving immunosuppressive or steroid treatments. Compared to AY.29 wild type, a total of 12 mutations were found in the 20 cases. Haplotype analysis found one index group of eight cases with F274F (N) mutation and 10 other haplotypes with one to three additional mutations. Furthermore, we found that cases with more than three minor variants were all cancer patients under immunosuppressive treatments. The phylogenetical tree analysis, including 20 nosocomial cluster-associated viral genomes, the first wild-type strain and the AY.29 wild-type strain as references, indicated the mutation development of the AY.29 virus in this cluster.

Conclusion

Our study of a nosocomial SARS-CoV-2 cluster highlights mutation acquisition during transmission. More importantly, it provided new evidence emphasizing the need to further improve infection control measures to prevent nosocomial infection among immunosuppressed patients.

Temporal dynamics of SARS-CoV-2 genome mutations that occurred in vivo on an aircraft

We analyzed variations in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome during a flight-related cluster outbreak of coronavirus disease 2019 (COVID-19) in Shenzhen, China, to explore the characteristics of SARS-CoV-2 transmission and intra-host single nucleotide variations (iSNVs) in a confined space. Thirty-three patients with COVID-19 were sampled, and 14 were resampled 3-31 days later. All 47 nasopharyngeal swabs were deep-sequenced. iSNVs and similarities in the consensus genome sequence were analyzed. Three SARS-CoV-2 variants of concern, Delta (n = 31), Beta (n = 1), and C.1.2 (n = 1), were detected among the 33 patients. The viral genome sequences from 30 Delta-positive patients had similar SNVs; 14 of these patients provided two successive samples. Overall, the 47 sequenced genomes contained 164 iSNVs. Of the 14 paired (successive) samples, the second samples (T2) contained more iSNVs (median: 3; 95% confidence interval [95% CI]: 2.77-10.22) than did the first samples (T1; median: 2; 95% CI: 1.63-3.74; Wilcoxon test, P = 0.021). 38 iSNVs were detected in T1 samples, and only seven were also detectable in T2 samples. Notably, T2 samples from two of the 14 paired samples had additional mutations than the T1 samples. The iSNVs of the SARS-CoV-2 genome exhibited rapid dynamic changes during a flight-related cluster outbreak event. Intra-host diversity increased gradually with time, and new site mutations occurred in vivo without a population transmission bottleneck. Therefore, we could not determine the generational relationship from the mutation site changes alone.

L-shaped distribution of the relative substitution rate (c/μ) observed for SARS-COV-2's genome, inconsistent with the selectionist theory, the neutral theory and the nearly neutral theory but a near-neutral balanced selection theory: Implication on "neutralist-selectionist" debate

The genomic substitution rate (GSR) of SARS-CoV-2 exhibits a molecular clock feature and does not change under fluctuating environmental factors such as the infected human population (10°-107), vaccination etc. The molecular clock feature is believed to be inconsistent with the selectionist theory (ST). The GSR shows lack of dependence on the effective population size, suggesting Ohta's nearly neutral theory (ONNT) is not applicable to this virus. Big variation of the substitution rate within its genome is also inconsistent with Kimura's neutral theory (KNT). Thus, all three existing evolution theories fail to explain the evolutionary nature of this virus. In this paper, we proposed a Segment Substitution Rate Model (SSRM) under non-neutral selections and pointed out that a balanced mechanism between negative and positive selection of some segments that could also lead to the molecular clock feature. We named this hybrid mechanism as near-neutral balanced selection theory (NNBST) and examined if it was followed by SARS-CoV-2 using the three independent sets of SARS-CoV-2 genomes selected by the Nextstrain team. Intriguingly, the relative substitution rate of this virus exhibited an L-shaped probability distribution consisting with NNBST rather than Poisson distribution predicted by KNT or an asymmetric distribution predicted by ONNT in which nearly neutral sites are believed to be slightly deleterious only, or the distribution that is lack of nearly neutral sites predicted by ST. The time-dependence of the substitution rates for some segments and their correlation with the vaccination were observed, supporting NNBST. Our relative substitution rate method provides a tool to resolve the long standing "neutralist-selectionist" controversy. Implications of NNBST in resolving Lewontin's Paradox is also discussed.

Assessing the hidden diversity underlying consensus sequences of SARS-CoV-2 using VICOS, a novel bioinformatic pipeline for identification of mixed viral populations

INTRODUCTION

Coinfection with two SARS-CoV-2 viruses is still a very understudied phenomenon. Although next generation sequencing methods are very sensitive to detect heterogeneous viral populations in a sample, there is no standardized method for their characterization, so their clinical and epidemiological importance is unknown.

MATERIAL AND METHODS

We developed VICOS (Viral COinfection Surveillance), a new bioinformatic algorithm for variant calling, filtering and statistical analysis to identify samples suspected of being mixed SARS-CoV-2 populations from a large dataset in the framework of a community genomic surveillance. VICOS was used to detect SARS-CoV-2 coinfections in a dataset of 1,097 complete genomes collected between March 2020 and August 2021 in Argentina.

RESULTS

We detected 23 cases (2%) of SARS-CoV-2 coinfections. Detailed study of VICOS's results together with additional phylogenetic analysis revealed 3 cases of coinfections by two viruses of the same lineage, 2 cases by viruses of different genetic lineages, 13 were compatible with both coinfection and intra-host evolution, and 5 cases were likely a product of laboratory contamination.

DISCUSSION

Intra-sample viral diversity provides important information to understand the transmission dynamics of SARS-CoV-2. Advanced bioinformatics tools, such as VICOS, are a necessary resource to help unveil the hidden diversity of SARS-CoV-2.

Tracking of Mutational Signature of SARS-CoV-2 Omicron on Distinct Continents and Little Difference was Found

The Omicron variant is currently ravaging the world, raising serious concern globally. Monitoring genomic variations and determining their influence on biological features are critical for tracing its ongoing transmission and facilitating effective measures. Based on large-scale sequences from different continents, this study found that: (i) The genetic diversity of Omicron is much lower than that of the Delta variant. Still, eight deletions (Del 1-8) and 1 insertion, as well as 130 SNPs, were detected on the Omicron genomes, with two deletions (Del 3 and 4) and 38 SNPs commonly detected on all continents and exhibiting high-occurring frequencies. (ii) Four groups of tightly linked SNPs (linkage I-IV) were detected, among which linkage I, containing 38 SNPs, with 6 located in the RBD, increased its occurring frequency remarkably over time. (iii) The third codons of the Omicron shouldered the most mutation pressures, while the second codons presented the least flexibility. (iv) Four major mutants with amino acid substitutions in the RBD were detected, and further structural analysis suggested that the substitutions did not alter the viral receptor binding ability greatly. It was inferred that though the Omicron genome harbored great changes in antigenicity and remarkable ability to evade immunity, it was immune-pressure selected. This study tracked mutational signatures of Omicron variant and the potential biological significance of the SNPs, and the linkages await further functional verification.

Rapid transmission and tight bottlenecks constrain the evolution of highly transmissible SARS-CoV-2 variants

Transmission bottlenecks limit the spread of novel mutations and reduce the efficiency of selection along a transmission chain. While increased force of infection, receptor binding, or immune evasion may influence bottleneck size, the relationship between transmissibility and the transmission bottleneck is unclear. Here we compare the transmission bottleneck of non-VOC SARS-CoV-2 lineages to those of Alpha, Delta, and Omicron. We sequenced viruses from 168 individuals in 65 households. Most virus populations had 0-1 single nucleotide variants (iSNV). From 64 transmission pairs with detectable iSNV, we identify a per clade bottleneck of 1 (95% CI 1-1) for Alpha, Delta, and Omicron and 2 (95% CI 2-2) for non-VOC. These tight bottlenecks reflect the low diversity at the time of transmission, which may be more pronounced in rapidly transmissible variants. Tight bottlenecks will limit the development of highly mutated VOC in transmission chains, adding to the evidence that selection over prolonged infections may drive their evolution.

SARS-CoV-2 Genomic Diversity in Households Highlights the Challenges of Sequence-Based Transmission Inference

The reliability of sequence-based inference of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission is not clear. Sequence data from infections among household members can define the expected genomic diversity of a virus along a defined transmission chain. SARS-CoV-2 cases were identified prospectively among 2,369 participants in 706 households. Specimens with a reverse transcription-PCR cycle threshold of ≤30 underwent whole-genome sequencing. Intrahost single-nucleotide variants (iSNV) were identified at a ≥5% frequency. Phylogenetic trees were used to evaluate the relationship of household and community sequences. There were 178 SARS-CoV-2 cases in 706 households. Among 147 specimens sequenced, 106 yielded a whole-genome consensus with coverage suitable for identifying iSNV. Twenty-six households had sequences from multiple cases within 14 days. Consensus sequences were indistinguishable among cases in 15 households, while 11 had ≥1 consensus sequence that differed by 1 to 2 mutations. Sequences from households and the community were often interspersed on phylogenetic trees. Identification of iSNV improved inference in 2 of 15 households with indistinguishable consensus sequences and in 6 of 11 with distinct ones. In multiple-infection households, whole-genome consensus sequences differed by 0 to 1 mutations. Identification of shared iSNV occasionally resolved linkage, but the low genomic diversity of SARS-CoV-2 limits the utility of "sequence-only" transmission inference. IMPORTANCE We performed whole-genome sequencing of SARS-CoV-2 from prospectively identified cases in three longitudinal household cohorts. In a majority of multi-infection households, SARS-CoV-2 consensus sequences were indistinguishable, and they differed by 1 to 2 mutations in the rest. Importantly, even with modest genomic surveillance of the community (3 to 5% of cases sequenced), it was not uncommon to find community sequences interspersed with household sequences on phylogenetic trees. Identification of shared minority variants only occasionally resolved these ambiguities in transmission linkage. Overall, the low genomic diversity of SARS-CoV-2 limits the utility of "sequence-only" transmission inference. Our work highlights the need to carefully consider both epidemiologic linkage and sequence data to define transmission chains in households, hospitals, and other transmission settings.

Multiple Mutations Associated with Emergent Variants Can Be Detected as Low-Frequency Mutations in Early SARS-CoV-2 Pandemic Clinical Samples

Genetic analysis of intra-host viral populations provides unique insight into pre-emergent mutations that may contribute to the genotype of future variants. Clinical samples positive for SARS-CoV-2 collected in California during the first months of the pandemic were sequenced to define the dynamics of mutation emergence as the virus became established in the state. Deep sequencing of 90 nasopharyngeal samples showed that many mutations associated with the establishment of SARS-CoV-2 globally were present at varying frequencies in a majority of the samples, even those collected as the virus was first detected in the US. A subset of mutations that emerged months later in consensus sequences were detected as subconsensus members of intra-host populations. Spike mutations P681H, H655Y, and V1104L were detected prior to emergence in variant genotypes, mutations were detected at multiple positions within the furin cleavage site, and pre-emergent mutations were identified in the nucleocapsid and the envelope genes. Because many of the samples had a very high depth of coverage, a bioinformatics pipeline, "Mappgene", was established that uses both iVar and LoFreq variant calling to enable identification of very low-frequency variants. This enabled detection of a spike protein deletion present in many samples at low frequency and associated with a variant of concern.

SARS-CoV-2 infection and persistence in the human body and brain at autopsy

Coronavirus disease 2019 (COVID-19) is known to cause multi-organ dysfunction1-3 during acute infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with some patients experiencing prolonged symptoms, termed post-acute sequelae of SARS-CoV-2 (refs. 4,5). However, the burden of infection outside the respiratory tract and time to viral clearance are not well characterized, particularly in the brain3,6-14. Here we carried out complete autopsies on 44 patients who died with COVID-19, with extensive sampling of the central nervous system in 11 of these patients, to map and quantify the distribution, replication and cell-type specificity of SARS-CoV-2 across the human body, including the brain, from acute infection to more than seven months following symptom onset. We show that SARS-CoV-2 is widely distributed, predominantly among patients who died with severe COVID-19, and that virus replication is present in multiple respiratory and non-respiratory tissues, including the brain, early in infection. Further, we detected persistent SARS-CoV-2 RNA in multiple anatomic sites, including throughout the brain, as late as 230 days following symptom onset in one case. Despite extensive distribution of SARS-CoV-2 RNA throughout the body, we observed little evidence of inflammation or direct viral cytopathology outside the respiratory tract. Our data indicate that in some patients SARS-CoV-2 can cause systemic infection and persist in the body for months.

SARS-CoV-2 induces "cytokine storm" hyperinflammatory responses in RA patients through pyroptosis

Background

The coronavirus disease (COVID-19) is a pandemic disease that threatens worldwide public health, and rheumatoid arthritis (RA) is the most common autoimmune disease. COVID-19 and RA are each strong risk factors for the other, but their molecular mechanisms are unclear. This study aims to investigate the biomarkers between COVID-19 and RA from the mechanism of pyroptosis and find effective disease-targeting drugs.

Methods

We obtained the common gene shared by COVID-19, RA (GSE55235), and pyroptosis using bioinformatics analysis and then did the principal component analysis(PCA). The Co-genes were evaluated by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and ClueGO for functional enrichment, the protein-protein interaction (PPI) network was built by STRING, and the k-means machine learning algorithm was employed for cluster analysis. Modular analysis utilizing Cytoscape to identify hub genes, functional enrichment analysis with Metascape and GeneMANIA, and NetworkAnalyst for gene-drug prediction. Network pharmacology analysis was performed to identify target drug-related genes intersecting with COVID-19, RA, and pyroptosis to acquire Co-hub genes and construct transcription factor (TF)-hub genes and miRNA-hub genes networks by NetworkAnalyst. The Co-hub genes were validated using GSE55457 and GSE93272 to acquire the Key gene, and their efficacy was assessed using receiver operating curves (ROC); SPEED2 was then used to determine the upstream pathway. Immune cell infiltration was analyzed using CIBERSORT and validated by the HPA database. Molecular docking, molecular dynamics simulation, and molecular mechanics-generalized born surface area (MM-GBSA) were used to explore and validate drug-gene relationships through computer-aided drug design.

Results

COVID-19, RA, and pyroptosis-related genes were enriched in pyroptosis and pro-inflammatory pathways(the NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome complex, death-inducing signaling complex, regulation of interleukin production), natural immune pathways (Network map of SARS-CoV-2 signaling pathway, activation of NLRP3 inflammasome by SARS-CoV-2) and COVID-19-and RA-related cytokine storm pathways (IL, nuclear factor-kappa B (NF-κB), TNF signaling pathway and regulation of cytokine-mediated signaling). Of these, CASP1 is the most involved pathway and is closely related to minocycline. YY1, hsa-mir-429, and hsa-mir-34a-5p play an important role in the expression of CASP1. Monocytes are high-caspase-1-expressing sentinel cells. Minocycline can generate a highly stable state for biochemical activity by docking closely with the active region of caspase-1.

Conclusions

Caspase-1 is a common biomarker for COVID-19, RA, and pyroptosis, and it may be an important mediator of the excessive inflammatory response induced by SARS-CoV-2 in RA patients through pyroptosis. Minocycline may counteract cytokine storm inflammation in patients with COVID-19 combined with RA by inhibiting caspase-1 expression.