Intra-host Diversity Research Articles

Immunosuppression as a Hub for SARS-CoV-2 Mutational Drift.

The clinical course of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is largely determined by host factors, with a wide range of outcomes. Despite an extensive vaccination campaign and high rates of infection worldwide, the pandemic persists, adapting to overcome antiviral immunity acquired through prior exposure. The source of many such major adaptations is variants of concern (VOCs), novel SARS-CoV-2 variants produced by extraordinary evolutionary leaps whose origins remain mostly unknown. In this study, we tested the influence of factors on the evolutionary course of SARS-CoV-2. Electronic health records of individuals infected with SARS-CoV-2 were paired to viral whole-genome sequences to assess the effects of host clinical parameters and immunity on the intra-host evolution of SARS-CoV-2. We found slight, albeit significant, differences in SARS-CoV-2 intra-host diversity, which depended on host parameters such as vaccination status and smoking. Only one viral genome had significant alterations as a result of host parameters; it was found in an immunocompromised, chronically infected woman in her 70s. We highlight the unusual viral genome obtained from this woman, which had an accelerated mutational rate and an excess of rare mutations, including near-complete truncating of the accessory protein ORF3a. Our findings suggest that the evolutionary capacity of SARS-CoV-2 during acute infection is limited and mostly unaffected by host characteristics. Significant viral evolution is seemingly exclusive to a small subset of COVID-19 cases, which typically prolong infections in immunocompromised patients. In these rare cases, SARS-CoV-2 genomes accumulate many impactful and potentially adaptive mutations; however, the transmissibility of such viruses remains unclear.

Signatures of natural selection in tree topology shape of serially sampled viral phylogenies

Tree shape metrics can be computed fast for trees of any size, which makes them promising alternatives to intensive statistical methods and parameter-rich evolutionary models in the era of massive data availability. Previous studies have demonstrated their effectiveness in unveiling important parameters in viral evolutionary dynamics, although the impact of natural selection on the shape of tree topologies has not been thoroughly investigated. We carried out a forward-time and individual-based simulation to investigate whether tree shape metrics of several kinds could predict the selection regime employed to generate the data. To examine the impact of the genetic diversity of the founder viral population, simulations were run under two opposing starting configurations of the genetic diversity of the infecting viral population. We found that four evolutionary regimes, namely, negative, positive, and frequency-dependent selection, as well as neutral evolution, were successfully distinguished by tree topology shape metrics. Two metrics from the Laplacian spectral density profile (principal eigenvalue and peakedness) and the number of cherries were the most informative for indicating selection type. The genetic diversity of the founder population had an impact on differentiating evolutionary scenarios. Tree imbalance, which has been frequently associated with the action of natural selection on intrahost viral diversity, was also characteristic of neutrally evolving serially sampled data. Metrics calculated from empirical analysis of HIV datasets indicated that most tree topologies exhibited shapes closer to the frequency-dependent selection or neutral evolution regimes.

ViReMa: a virus recombination mapper of next-generation sequencing data characterizes diverse recombinant viral nucleic acids.

Genetic recombination is a tremendous source of intrahost diversity in viruses and is critical for their ability to rapidly adapt to new environments or fitness challenges. While viruses are routinely characterized using high-throughput sequencing techniques, characterizing the genetic products of recombination in next-generation sequencing data remains a challenge. Viral recombination events can be highly diverse and variable in nature, including simple duplications and deletions, or more complex events such as copy/snap-back recombination, intervirus or intersegment recombination, and insertions of host nucleic acids. Due to the variable mechanisms driving virus recombination and the different selection pressures acting on the progeny, recombination junctions rarely adhere to simple canonical sites or sequences. Furthermore, numerous different events may be present simultaneously in a viral population, yielding a complex mutational landscape. We have previously developed an algorithm called ViReMa (Virus Recombination Mapper) that bootstraps the bowtie short-read aligner to capture and annotate a wide range of recombinant species found within virus populations. Here, we have updated ViReMa to provide an "error density" function designed to accurately detect recombination events in the longer reads now routinely generated by the Illumina platforms and provide output reports for multiple types of recombinant species using standardized formats. We demonstrate the utility and flexibility of ViReMa in different settings to report deletion events in simulated data from Flock House virus, copy-back RNA species in Sendai viruses, short duplication events in HIV, and virus-to-host recombination in an archaeal DNA virus.

Vaccination against swine influenza in pigs causes different drift evolutionary patterns upon swine influenza virus experimental infection and reduces the likelihood of genomic reassortments.

Influenza A viruses (IAVs) can infect a wide variety of bird and mammal species. Their genome is characterized by 8 RNA single stranded segments. The low proofreading activity of their polymerases and the genomic reassortment between different IAVs subtypes allow them to continuously evolve, constituting a constant threat to human and animal health. In 2009, a pandemic of an IAV highlighted the importance of the swine host in IAVs adaptation between humans and birds. The swine population and the incidence of swine IAV is constantly growing. In previous studies, despite vaccination, swine IAV growth and evolution were proven in vaccinated and challenged animals. However, how vaccination can drive the evolutionary dynamics of swine IAV after coinfection with two subtypes is poorly studied. In the present study, vaccinated and nonvaccinated pigs were challenged by direct contact with H1N1 and H3N2 independent swine IAVs seeder pigs. Nasal swab samples were daily recovered and broncho-alveolar lavage fluid (BALF) was also collected at necropsy day from each pig for swine IAV detection and whole genome sequencing. In total, 39 swine IAV whole genome sequences were obtained by next generation sequencing from samples collected from both experimental groups. Subsequently, genomic, and evolutionary analyses were carried out to detect both, genomic reassortments and single nucleotide variants (SNV). Regarding the segments found per sample, the simultaneous presence of segments from both subtypes was much lower in vaccinated animals, indicating that the vaccine reduced the likelihood of genomic reassortment events. In relation to swine IAV intra-host diversity, a total of 239 and 74 SNV were detected within H1N1 and H3N2 subtypes, respectively. Different proportions of synonymous and nonsynonymous substitutions were found, indicating that vaccine may be influencing the main mechanism that shape swine IAV evolution, detecting natural, neutral, and purifying selection in the different analyzed scenarios. SNV were detected along the whole swine IAV genome with important nonsynonymous substitutions on polymerases, surface glycoproteins and nonstructural proteins, which may have an impact on virus replication, immune system escaping and virulence of virus, respectively. The present study further emphasized the vast evolutionary capacity of swine IAV, under natural infection and vaccination pressure scenarios.

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 471days (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.

Challenges in Harnessing Shared Within-Host Severe Acute Respiratory Syndrome Coronavirus 2 Variation for Transmission Inference.

The limited variation observed among severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) consensus sequences makes it difficult to reconstruct transmission linkages in outbreak settings. Previous studies have recovered variation within individual SARS-CoV-2 infections but have not yet measured the informativeness of within-host variation for transmission inference. We performed tiled amplicon sequencing on 307 SARS-CoV-2 samples, including 130 samples from 32 individuals in 14 households and 47 longitudinally sampled individuals, from 4 prospective studies with household membership data, a proxy for transmission linkage. Consensus sequences from households had limited diversity (mean pairwise distance, 3.06 single-nucleotide polymorphisms [SNPs]; range, 0-40). Most (83.1%, 255 of 307) samples harbored at least 1 intrahost single-nucleotide variant ([iSNV] median, 117; interquartile range [IQR], 17-208), above a minor allele frequency threshold of 0.2%. Pairs in the same household shared significantly more iSNVs (mean, 1.20 iSNVs; 95% confidence interval [CI], 1.02-1.39) than did pairs in different households infected with the same viral clade (mean, 0.31 iSNVs; 95% CI, .28-.34), a signal that decreases with increasingly stringent minor allele frequency thresholds. The number of shared iSNVs was significantly associated with an increased odds of household membership (adjusted odds ratio, 1.35; 95% CI, 1.23-1.49). However, the poor concordance of iSNVs detected across sequencing replicates (24.8% and 35.0% above a 0.2% and 1% threshold) confirms technical concerns that current sequencing and bioinformatic workflows do not consistently recover low-frequency within-host variants. Shared within-host variation may augment the information in consensus sequences for predicting transmission linkages. Improving sensitivity and specificity of within-host variant identification will improve the informativeness of within-host variation.

Deep-sequencing of viral genomes from a large and diverse cohort of treatment-naive HIV-infected persons shows associations between intrahost genetic diversity and viral load.

Infection with human immunodeficiency virus type 1 (HIV) typically results from transmission of a small and genetically uniform viral population. Following transmission, the virus population becomes more diverse because of recombination and acquired mutations through genetic drift and selection. Viral intrahost genetic diversity remains a major obstacle to the cure of HIV; however, the association between intrahost diversity and disease progression markers has not been investigated in large and diverse cohorts for which the majority of the genome has been deep-sequenced. Viral load (VL) is a key progression marker and understanding of its relationship to viral intrahost genetic diversity could help design future strategies for HIV monitoring and treatment. We analysed deep-sequenced viral genomes from 2,650 treatment-naive HIV-infected persons to measure the intrahost genetic diversity of 2,447 genomic codon positions as calculated by Shannon entropy. We tested for associations between VL and amino acid (AA) entropy accounting for sex, age, race, duration of infection, and HIV population structure. We confirmed that the intrahost genetic diversity is highest in the env gene. Furthermore, we showed that mean Shannon entropy is significantly associated with VL, especially in infections of >24 months duration. We identified 16 significant associations between VL (p-value<2.0x10-5) and Shannon entropy at AA positions which in our association analysis explained 13% of the variance in VL. Finally, equivalent analysis based on variation in HIV consensus sequences explained only 2% of VL variance. Our results elucidate that viral intrahost genetic diversity is associated with VL and could be used as a better disease progression marker than HIV consensus sequence variants, especially in infections of longer duration. We emphasize that viral intrahost diversity should be considered when studying viral genomes and infection outcomes. Samples included in this study were derived from participants who consented in the clinical trial, START (NCT00867048) (23), run by the International Network for Strategic Initiatives in Global HIV Trials (INSIGHT). All the participant sites are listed here: http://www.insight-trials.org/start/my_phpscript/participating.php?by=site.

Genetic diversity of the dengue virus population in dengue fever and dengue hemorrhagic fever patients.

The error-prone replication of dengue virus (DENV) in host results in the highly diverse viral population. Together with the host factor, intra-host diversity may influence the disease severity. Therefore, it is worth investigating whether there is a correlation between intra-host genetic diversity and disease severity. To investigate the genetic diversity in DENV for four serotypes of the dengue population from patients with dengue fever (DF) and dengue hemorrhagic fever (DHF) using next-generation sequencing (NGS) technology. Forty RNA samples categorized into eight groups by severity and serotypes were sequenced and analyzed for genetic variation. Analysis on the hot-cold genomic regions, selection pressure and correlation between genotype and disease severity were performed in this study. Comparison between the NGS data of the DF and DHF specimens showed conservation between their major populations with the consensus sequences for DF and DHF sharing 99% similarity. However, the minor populations in DF and DHF were more diverse. Many genes in DF had an #NS/#S ratio higher than in DHF. Only NS4B of DENV1 DF has #NS/#S ratio higher than one. Hot regions of the DF were detected in NS3 of DENV1, DENV2 and Envelope of DENV3, whereas the hot regions of the DHF samples were detected in the small region in 3'UTR of DENV2 and DENV3. Various explorations of the variations of DF and DHF were performed in this study. However, we have not yet found any specific characteristics of intra-host diversity associated with disease severity.

Inter-host Genetic Variability of Severe Acute Respiratory Syndrome Coronavirus 2 and its Implication in Biomedicine: A Bioinformatics Approach

Abstract Background: Genomic sequencing data from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have provided important information on the emergence of variants of interest. Some research has focused on determining intra-host variability and evolution, and others have focused on viral genetic variability in different tissues, as well as implications for virus infectivity and pathogenicity. However, the inter-host variability of SARS-CoV-2 in respiratory compartments and its implications has not yet been explained. To determine a possible pattern of tissue-specific inter-host variability at different levels of the respiratory system associating this information with clinically important characteristics. Methods: In this work, we analyzed the inter-host variability of SARS-CoV-2 using the Shannon entropy method with genomic data from NCBI database. Fifty-seven SARS-CoV-2 viral genomic sequences were included in the study. Oronasopharyngeal (n = 30) and tracheal aspirate (n = 27) sample sequences were analyzed by bioinformatics methods to determine the viral variability. Results: Different patterns of variability were observed in SARS-CoV-2 in the respiratory tract, which may indicate tissue compartmentalization phenomena. Genetic changes found in the N y S gene could affect the detection and spread of the virus. The overall analysis of the viral genomes identifies the variants of worldwide distribution. The viral diversity found in the different parts of the respiratory tract was high and uniformly distributed throughout the genome. Conclusions: Tracking inter-host variations in SARS-CoV-2 could help to understand the effects of viral evolution, provide information for diagnosis, drug, and vaccine design.

Quasispecies Analysis of SARS-CoV-2 of 15 Different Lineages during the First Year of the Pandemic Prompts Scratching under the Surface of Consensus Genome Sequences.

The tremendous majority of SARS-CoV-2 genomic data so far neglected intra-host genetic diversity. Here, we studied SARS-CoV-2 quasispecies based on data generated by next-generation sequencing (NGS) of complete genomes. SARS-CoV-2 raw NGS data had been generated for nasopharyngeal samples collected between March 2020 and February 2021 by the Illumina technology on a MiSeq instrument, without prior PCR amplification. To analyze viral quasispecies, we designed and implemented an in-house Excel file (“QuasiS”) that can characterize intra-sample nucleotide diversity along the genomes using data of the mapping of NGS reads. We compared intra-sample genetic diversity and global genetic diversity available from Nextstrain. Hierarchical clustering of all samples based on the intra-sample genetic diversity was performed and visualized with the Morpheus web application. NGS mapping data from 110 SARS-CoV-2-positive respiratory samples characterized by a mean depth of 169 NGS reads/nucleotide position and for which consensus genomes that had been obtained were classified into 15 viral lineages were analyzed. Mean intra-sample nucleotide diversity was 0.21 ± 0.65%, and 5357 positions (17.9%) exhibited significant (>4%) diversity, in ≥2 genomes for 1730 (5.8%) of them. ORF10, spike, and N genes had the highest number of positions exhibiting diversity (0.56%, 0.34%, and 0.24%, respectively). Nine hot spots of intra-sample diversity were identified in the SARS-CoV-2 NSP6, NSP12, ORF8, and N genes. Hierarchical clustering delineated a set of six genomes of different lineages characterized by 920 positions exhibiting intra-sample diversity. In addition, 118 nucleotide positions (0.4%) exhibited diversity at both intra- and inter-patient levels. Overall, the present study illustrates that the SARS-CoV-2 consensus genome sequences are only an incomplete and imperfect representation of the entire viral population infecting a patient, and that quasispecies analysis may allow deciphering more accurately the viral evolutionary pathways.

Distribution of intra-host variations and mutations in the genomes of SARS-CoV-2 and their implications on detection and therapeutics.

The ongoing circulation of SARS-CoV-2 variants of concern (VOCs) has caused global concerns, because VOCs could escape current vaccines, antiviral drugs, and diagnosis. Analyzing mutations and intra-host diversities in different and widespread VOCs can provide important insights to virus adaptive evolution and validity of vaccines, antiviral drugs, and diagnosis. In this study, by analyzing 1744 high-throughput sequencing data for intra-host single-nucleotide variations (iSNVs) and 3,668,205 genome sequences for mutations in different VOCs, it was found that Omicron variant is still evolving at high speed, especially having high iSNVs frequency in its S and N genes. The efficacies of antibodies or detection primers targeting these two genes are at high risks to be invalid. Instead, highly conserved regions such as NSP8 gene could be better therapeutic and detection targets. Furthermore, mutations in later VOCs could be traced to the minor alleles in the previous variant samples such as Alpha and Delta in different countries. Finally, it was found that mutations C14408T in RdRp and A18163G in NSP14 gene might be associated with the higher genetic diversity in Omicron. Our findings not only contribute to understanding the adaptive evolution of SARS-CoV-2 VOCs, but also provide useful information for both drugs and diagnostic kits development.

SARS-CoV-2 intra-host single-nucleotide variants associated with disease severity.

Variants of severe acute respiratory syndrome coronavirus 2 frequently arise within infected individuals. Here, we explored the level and pattern of intra-host viral diversity in association with disease severity. Then, we analyzed information underlying these nucleotide changes to infer the impetus including mutational signatures and immune selection from neutralizing antibody or T-cell recognition. From 23 January to 31 March 2020, a set of cross-sectional samples were collected from individuals with homogeneous founder virus regardless of disease severity. Intra-host single-nucleotide variants (iSNVs) were enumerated using deep sequencing. Human leukocyte antigen (HLA) alleles were genotyped by Sanger sequencing. Medical records were collected and reviewed by attending physicians. A total of 836 iSNVs (3-106 per sample) were identified and distributed in a highly individualized pattern. The number of iSNVs paced with infection duration peaked within days and declined thereafter. These iSNVs did not stochastically arise due to a strong bias toward C > U/G > A and U > C/A > G substitutions in reciprocal proportion with escalating disease severity. Eight nonsynonymous iSNVs in the receptor-binding domain could escape from neutralization, and eighteen iSNVs were significantly associated with specific HLA alleles. The level and pattern of iSNVs reflect the in vivo viral-host interaction and the disease pathogenesis.

High-Risk Oncogenic Human Cytomegalovirus.

Human cytomegalovirus (HCMV) is a herpesvirus that infects between 40% and 95% of the population worldwide, usually without symptoms. The host immune response keeps the virus in a latent stage, although HCMV can reactivate in an inflammatory context, which could result in sequential lytic/latent viral cycles during the lifetime and thereby participate in HCMV genomic diversity in humans. The high level of HCMV intra-host genomic variability could participate in the oncomodulatory role of HCMV where the virus will favor the development and spread of cancerous cells. Recently, an oncogenic role of HCMV has been highlighted in which the virus will directly transform primary cells; such HCMV strains are named high-risk (HR) HCMV strains. In light of these new findings, this review defines the criteria that characterize HR-HCMV strains and their molecular as well as the phenotypic impact on the infected cell and its tumor microenvironment.

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.

Comparative analysis of within-host diversity among vaccinated COVID-19 patients infected with different SARS-CoV-2 variants

SARS-CoV-2 is a rapidly evolving RNA virus that mutates within hosts and exists as viral quasispecies. Here, we evaluated the within-host diversity among vaccinated and unvaccinated individuals (n=379) infected with different SARS-CoV-2 variants of concern. The majority of samples harbored less than 14 iSNVs. Deep analysis revealed a significantly higher intra-host diversity in Omicron samples compared to other variants (p-value < 0.05). Vaccination status and type had a limited impact on intra-host diversity except for Beta-B.1.315 and Delta-B.1.617.2 vaccinees, who exhibited higher diversity compared to unvaccinated individuals (p-values: < 0.0001 and < 0.0021; respectively). Three immune-escape mutations were identified: S255F in Delta; and R346K and T376A in Omicron-B.1.1.529. The latter two mutations were fixed in BA.1 and BA.2 genomes, respectively. Overall, the relatively higher intra-host diversity among vaccinated individuals, and the detection of immune-escape mutations, despite rare, suggest a potential vaccine-induced immune pressure in vaccinated individuals.

Identifying high-confidence variants in human cytomegalovirus genomes sequenced from clinical samples.

Understanding the intrahost evolution of viral populations has implications in pathogenesis, diagnosis, and treatment and has recently made impressive advances from developments in high-throughput sequencing. However, the underlying analyses are very sensitive to sources of bias, error, and artefact in the data, and it is important that these are addressed adequately if robust conclusions are to be drawn. The key factors include (1) determining the number of viral strains present in the sample analysed; (2) monitoring the extent to which the data represent these strains and assessing the quality of these data; (3) dealing with the effects of cross-contamination; and (4) ensuring that the results are reproducible. We investigated these factors by generating sequence datasets, including biological and technical replicates, directly from clinical samples obtained from a small cohort of patients who had been infected congenitally with the herpesvirus human cytomegalovirus, with the aim of developing a strategy for identifying high-confidence intrahost variants. We found that such variants were few in number and typically present in low proportions and concluded that human cytomegalovirus exhibits a very low level of intrahost variability. In addition to clarifying the situation regarding human cytomegalovirus, our strategy has wider applicability to understanding the intrahost variability of other viruses.

A combined approach of rolling-circle amplification-single site restriction endonuclease digestion followed by next generation sequencing to characterize the whole genome and intra-host variants of human Torque teno virus

Torque Teno Virus (TTV) was initially associated with post-transfusion hepatitis, but growing evidence of its ubiquity in humans is compatible to no apparent clinical significance. TTV is a small non-enveloped virus with a circular single-negative-stranded DNA genome, belonging to the Anelloviridae family. Currently, TTVs are divided in seven phylogenetic groups and are further classified into 21 species. Studies about diversity of TTV in different conditions are receiving increasing interest and in this sense, sequencing of whole genomes for better genetic characterization becomes even more important. Since its discovery in 1997, few TTV complete genomes have been reported worldwide. This is probably due, among other reasons, to the great genetic heterogeneity among TTV strains that prevents its amplification and sequencing by conventional PCR and cloning methods. In addition, although metagenomics approach is useful in these cases, it remains a challenging tool for viromic analysis. With the aim of contributing to the expansion of the TTV whole genomes dataset and to study intra-host variants, we employed a methodology that combined a rolling-circle amplification approach followed by EcoRI digestion, generating a DNA fragment of ∼4Kb consistent with TTV genome length which was sequenced by Illumina next generation sequencing. A genogroup 3 full-length consensus TTV genome was obtained and co-infection with other species (at least those with a single EcoRI cleavage site) was not identified. Additionally, bioinformatics analysis allowed to identify the spectrum of TTV intra-host variants which provides evidence of a complex evolution dynamics of these DNA circular viruses, similarly to what occurs with RNA viruses.

SOPHIE: Viral outbreak investigation and transmission history reconstruction in a joint phylogenetic and network theory framework.

Genomic epidemiology is now widely used for viral outbreak investigations. Still, this methodology faces many challenges. First, few methods account for intra-host viral diversity. Second, maximum parsimony principle continues to be employed for phylogenetic inference of transmission histories, even though maximum likelihood or Bayesian models are usually more consistent. Third, many methods utilize case-specific data, such as sampling times or infection exposure intervals. This impedes study of persistent infections in vulnerable groups, where such information has a limited use. Finally, most methods implicitly assume that transmission events are independent, although common source outbreaks violate this assumption. We propose a maximum likelihood framework, SOPHIE, based on the integration of phylogenetic and random graph models. It infers transmission networks from viral phylogenies and expected properties of inter-host social networks modeled as random graphs with given expected degree distributions. SOPHIE is scalable, accounts for intra-host diversity, and accurately infers transmissions without case-specificepidemiological data.

Intrahost SARS-CoV-2 k-mer Identification Method (iSKIM) for Rapid Detection of Mutations of Concern Reveals Emergence of Global Mutation Patterns

Despite unprecedented global sequencing and surveillance of SARS-CoV-2, timely identification of the emergence and spread of novel variants of concern (VoCs) remains a challenge. Several million raw genome sequencing runs are now publicly available. We sought to survey these datasets for intrahost variation to study emerging mutations of concern. We developed iSKIM (“intrahost SARS-CoV-2 k-mer identification method”) to relatively quickly and efficiently screen the many SARS-CoV-2 datasets to identify intrahost mutations belonging to lineages of concern. Certain mutations surged in frequency as intrahost minor variants just prior to, or while lineages of concern arose. The Spike N501Y change common to several VoCs was found as a minor variant in 834 samples as early as October 2020. This coincides with the timing of the first detected samples with this mutation in the Alpha/B.1.1.7 and Beta/B.1.351 lineages. Using iSKIM, we also found that Spike L452R was detected as an intrahost minor variant as early as September 2020, prior to the observed rise of the Epsilon/B.1.429/B.1.427 lineages in late 2020. iSKIM rapidly screens for mutations of interest in raw data, prior to genome assembly, and can be used to detect increases in intrahost variants, potentially providing an early indication of novel variant spread.

Genome analysis of Psilogramma increta granulovirus and its intrapopulation diversity

The complete genome of Psilogramma increta granulovirus (PsinGV), isolated from P. increta (Lepidoptera: Sphingidae), was ultra-deep sequenced with a Novaseq PE150 platform and de novo assembled and annotated. The PsinGV genome is a circular double-stranded DNA, 103,721 bp in length, with a G+C content of 33.0%, the third lowest G+C content in present sequenced baculoviruses. It encodes 123 putative open reading frames, including 38 baculovirus core genes, 42 lepidopteran baculovirus conserved genes, 38 betabaculovirus conserved genes, and 5 genes unique to PsinGV. Meanwhile, 3 homologous repeated regions with the core sequence TTGCAA and 3 direct repeated sequences were identified within the PsinGV genome. Kimura two-parameters distance analysis confirmed that Psilogramma increta granulovirus is a representative of a prospective new species of the genus Betabaculovirus. Phylogenetic analysis based on the baculovirus core genes showed that PsinGV is closely related to Choristoneura fumiferana granulovirus, Clostera anastomosis granulovirus-B, and Erinnyis ello granulovirus. These four species therefore share a common ancestor residing in the Betabaculovirus genus. The genome of the PsinGV isolate contained two p10 copies: p10 and p10-2. Phylogenetic reconstruction of P10 suggests a transfer event of the p10-2 gene from an alphabaculovirus to the aforementioned common ancestor. Analysis of genomic diversity showed that 203 intrahost variants, including 182 single nucleotide variants and 21 short insertions/deletions, are present within the PsinGV isolate. Meanwhile, allele frequency indicated that the isolate contains three major genotypes, implying the archived isolate consists of several P. increta carcasses killed by PsinGV with different genotypes.