Clinical Sequencing Uncovers Origins and Evolution of Lassa Virus.

The 2013-2015 West African epidemic of Ebola virus disease (EVD) reminds us of how little is known about biosafety level 4 viruses. Like Ebola virus, Lassa virus (LASV) can cause hemorrhagic fever with high case fatality rates. We generated a genomic catalog of almost 200 LASV sequences from clinical and rodent reservoir samples. We show that whereas the 2013-2015 EVD epidemic is fueled by human-to-human transmissions, LASV infections mainly result from reservoir-to-human infections. We elucidated the spread of LASV across West Africa and show that this migration was accompanied by changes in LASV genome abundance, fatality rates, codon adaptation, and translational efficiency. By investigating intrahost evolution, we found that mutations accumulate in epitopes of viral surface proteins, suggesting selection for immune escape. This catalog will serve as a foundation for the development of vaccines and diagnostics. VIDEO ABSTRACT.

Neoantigen vaccine generates intratumoral T cell responses in phase Ib glioblastoma trial.

Neoantigens, which are derived from tumour-specific protein-coding mutations, are exempt from central tolerance, can generate robust immune responses1,2 and can function as bona fide antigens that facilitate tumour rejection3. Here we demonstrate that a strategy that uses multi-epitope, personalized neoantigen vaccination, which has previously been tested in patients with high-risk melanoma4-6, is feasible for tumours such as glioblastoma, which typically have a relatively low mutation load1,7 and an immunologically 'cold' tumour microenvironment8. We used personalized neoantigen-targeting vaccines to immunize patients newly diagnosed with glioblastoma following surgical resection and conventional radiotherapy in a phase I/Ib study. Patients who did not receive dexamethasone-a highly potent corticosteroid that is frequently prescribed to treat cerebral oedema in patients with glioblastoma-generated circulating polyfunctional neoantigen-specific CD4+ and CD8+ T cell responses that were enriched in a memory phenotype and showed an increase in the number of tumour-infiltrating T cells. Using single-cell T cell receptor analysis, we provide evidence that neoantigen-specific T cells from the peripheral blood can migrate into an intracranial glioblastoma tumour. Neoantigen-targeting vaccines thus have the potential to favourably alter the immune milieu of glioblastoma.

Returning integrated genomic risk and clinical recommendations: The eMERGE study.

PURPOSE: Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk. METHODS: To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results. RESULTS: GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022. CONCLUSION: Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

Cross-Sectional Assessment of SARS-CoV-2 Viral Load by Symptom Status in Massachusetts Congregate Living Facilities.

Transmission of coronavirus disease 2019 (COVID-19) from people without symptoms confounds societal mitigation strategies. From April to June 2020, we tested nasopharyngeal swabs by reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) from 15 514 staff and 16 966 residents of nursing homes and assisted living facilities in Massachusetts. Cycle threshold (Ct) distributions were very similar between populations with (n = 739) and without (n = 2179) symptoms at the time of sampling (mean Ct, 25.7 vs 26.4; ranges 12-38). However, as local cases waned, those without symptoms shifted towards higher Ct. With such similar viral load distributions, existing testing modalities should perform comparably regardless of symptoms, contingent upon time since infection.

Implementation of SARS-CoV2 Screening in K-12 Schools Using In-School Pooled Molecular Testing and Deconvolution by Rapid Antigen Test.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) testing is one component of a multilayered mitigation strategy to enable safe in-person school attendance for the K-12 school population. However, costs, logistics, and uncertainty about effectiveness are potential barriers to implementation. We assessed early data from the Massachusetts K-12 public school pooled SARS-CoV2 testing program, which incorporates two novel design elements: in-school "pod pooling" for assembling pools of dry anterior nasal swabs from 5 to 10 individuals and positive pool deconvolution using the BinaxNOW antigen rapid diagnostic test (Ag RDT), to assess the operational and analytical feasibility of this approach. Over 3 months, 187,597 individual swabs were tested across 39,297 pools from 738 schools. The pool positivity rate was 0.8%; 98.2% of pools tested negative and 0.2% inconclusive, and 0.8% of pools submitted could not be tested. Of 310 positive pools, 70.6% had an N1 or N2 probe cycle threshold (CT) value of ≤30. In reflex testing (performed on specimens newly collected from members of the positive pool), 92.5% of fully deconvoluted pools with an N1 or N2 target CT of ≤30 identified a positive individual using the BinaxNOW test performed 1 to 3 days later. However, of 124 positive pools with full reflex testing data available for analysis, 32 (25.8%) of BinaxNOW pool deconvolution testing attempts did not identify a positive individual, requiring additional reflex testing. With sufficient staffing support and low pool positivity rates, pooled sample collection and reflex testing were feasible for schools. These early program findings confirm that screening for K-12 students and staff is achievable at scale with a scheme that incorporates in-school pooling, primary testing by reverse transcription-PCR (RT-PCR), and Ag RDT reflex/deconvolution testing.

Performance and Implementation Evaluation of the Abbott BinaxNOW Rapid Antigen Test in a High-Throughput Drive-Through Community Testing Site in Massachusetts.

Rapid diagnostic tests (RDTs) for SARS-CoV-2 antigens (Ag) that can be performed at point of care (POC) can supplement molecular testing and help mitigate the COVID-19 pandemic. Deployment of an Ag RDT requires an understanding of its operational and performance characteristics under real-world conditions and in relevant subpopulations. We evaluated the Abbott BinaxNOW COVID-19 Ag card in a high-throughput, drive-through, free community testing site in Massachusetts using anterior nasal (AN) swab reverse transcriptase PCR (RT-PCR) for clinical testing. Individuals presenting for molecular testing in two of seven lanes were offered the opportunity to also receive BinaxNOW testing. Dual AN swabs were collected from symptomatic and asymptomatic children (≤18 years of age) and adults. BinaxNOW testing was performed in a testing pod with temperature/humidity monitoring. One individual performed testing and official result reporting for each test, but most tests had a second independent reading to assess interoperator agreement. Positive BinaxNOW results were scored as faint, medium, or strong. Positive BinaxNOW results were reported to patients by phone, and they were instructed to isolate pending RT-PCR results. The paired RT-PCR result was the reference for sensitivity and specificity calculations. Of 2,482 participants, 1,380 adults and 928 children had paired RT-PCR/BinaxNOW results and complete symptom data. In this study, 974/1,380 (71%) adults and 829/928 (89%) children were asymptomatic. BinaxNOW had 96.5% (95% confidence interval [CI], 90.0 to 99.3) sensitivity and 100% (95% CI, 98.6 to 100.0) specificity in adults within 7 days of symptoms and 84.6% (95% CI, 65.1 to 95.6) sensitivity and 100% (95% CI, 94.5 to 100.0) specificity in children within 7 days of symptoms. Sensitivity and specificity in asymptomatic adults were 70.2% (95% CI, 56.6 to 81.6) and 99.6% (95% CI, 98.9 to 99.9), respectively, and in asymptomatic children, they were 65.4% (95% CI, 55.6 to 74.4) and 99.0% (95% CI, 98.0 to 99.6), respectively. By cycle threshold (CT ) value cutoff, sensitivity in all subgroups combined (n = 292 RT-PCR-positive individuals) was 99.3% with CT values of ≤25, 95.8% with CT values of ≤30, and 81.2% with CT values of ≤35. Twelve false-positive BinaxNOW results (out of 2,308 tests) were observed; in all 12, the test bands were faint but otherwise normal and were noted by both readers. One invalid BinaxNOW result was identified. Interoperator agreement (positive versus negative BinaxNOW result) was 100% (n = 2,230/2,230 double reads). Each operator was able to process 20 RDTs per hour. In a separate set of 30 specimens (from individuals with symptoms ≤7 days) run at temperatures below the manufacturer's recommended range (46 to 58.5°F), sensitivity was 66.7% and specificity 95.2%. BinaxNOW had very high specificity in both adults and children and very high sensitivity in newly symptomatic adults. Overall, 95.8% sensitivity was observed with CT values of ≤30. These data support public health recommendations for use of the BinaxNOW test in adults with symptoms for ≤7 days without RT-PCR confirmation. Excellent interoperator agreement indicates that an individual can perform and read the BinaxNOW test alone. A skilled laboratorian can perform and read 20 tests per hour. Careful attention to temperature is critical.

Characterization and remediation of sample index swaps by non-redundant dual indexing on massively parallel sequencing platforms.

BACKGROUND: Here we present an in-depth characterization of the mechanism of sequencer-induced sample contamination due to the phenomenon of index swapping that impacts Illumina sequencers employing patterned flow cells with Exclusion Amplification (ExAmp) chemistry (HiSeqX, HiSeq4000, and NovaSeq). We also present a remediation method that minimizes the impact of such swaps. RESULTS: Leveraging data collected over a two-year period, we demonstrate the widespread prevalence of index swapping in patterned flow cell data. We calculate mean swap rates across multiple sample preparation methods and sequencer models, demonstrating that different library methods can have vastly different swapping rates and that even non-ExAmp chemistry instruments display trace levels of index swapping. We provide methods for eliminating sample data cross contamination by utilizing non-redundant dual indexing for complete filtering of index swapped reads, and share the sequences for 96 non-combinatorial dual indexes we have validated across various library preparation methods and sequencer models. Finally, using computational methods we provide a greater insight into the mechanism of index swapping. CONCLUSIONS: Index swapping in pooled libraries is a prevalent phenomenon that we observe at a rate of 0.2 to 6% in all sequencing runs on HiSeqX, HiSeq 4000/3000, and NovaSeq. Utilizing non-redundant dual indexing allows for the removal (flagging/filtering) of these swapped reads and eliminates swapping induced sample contamination, which is critical for sensitive applications such as RNA-seq, single cell, blood biopsy using circulating tumor DNA, or clinical sequencing.

Differences in the Selection Bottleneck between Modes of Sexual Transmission Influence the Genetic Composition of the HIV-1 Founder Virus.

Due to the stringent population bottleneck that occurs during sexual HIV-1 transmission, systemic infection is typically established by a limited number of founder viruses. Elucidation of the precise forces influencing the selection of founder viruses may reveal key vulnerabilities that could aid in the development of a vaccine or other clinical interventions. Here, we utilize deep sequencing data and apply a genetic distance-based method to investigate whether the mode of sexual transmission shapes the nascent founder viral genome. Analysis of 74 acute and early HIV-1 infected subjects revealed that 83% of men who have sex with men (MSM) exhibit a single founder virus, levels similar to those previously observed in heterosexual (HSX) transmission. In a metadata analysis of a total of 354 subjects, including HSX, MSM and injecting drug users (IDU), we also observed no significant differences in the frequency of single founder virus infections between HSX and MSM transmissions. However, comparison of HIV-1 envelope sequences revealed that HSX founder viruses exhibited a greater number of codon sites under positive selection, as well as stronger transmission indices possibly reflective of higher fitness variants. Moreover, specific genetic "signatures" within MSM and HSX founder viruses were identified, with single polymorphisms within gp41 enriched among HSX viruses while more complex patterns, including clustered polymorphisms surrounding the CD4 binding site, were enriched in MSM viruses. While our findings do not support an influence of the mode of sexual transmission on the number of founder viruses, they do demonstrate that there are marked differences in the selection bottleneck that can significantly shape their genetic composition. This study illustrates the complex dynamics of the transmission bottleneck and reveals that distinct genetic bottleneck processes exist dependent upon the mode of HIV-1 transmission.

Medulloblastoma exome sequencing uncovers subtype-specific somatic mutations.

Medulloblastomas are the most common malignant brain tumours in children. Identifying and understanding the genetic events that drive these tumours is critical for the development of more effective diagnostic, prognostic and therapeutic strategies. Recently, our group and others described distinct molecular subtypes of medulloblastoma on the basis of transcriptional and copy number profiles. Here we use whole-exome hybrid capture and deep sequencing to identify somatic mutations across the coding regions of 92 primary medulloblastoma/normal pairs. Overall, medulloblastomas have low mutation rates consistent with other paediatric tumours, with a median of 0.35 non-silent mutations per megabase. We identified twelve genes mutated at statistically significant frequencies, including previously known mutated genes in medulloblastoma such as CTNNB1, PTCH1, MLL2, SMARCA4 and TP53. Recurrent somatic mutations were newly identified in an RNA helicase gene, DDX3X, often concurrent with CTNNB1 mutations, and in the nuclear co-repressor (N-CoR) complex genes GPS2, BCOR and LDB1. We show that mutant DDX3X potentiates transactivation of a TCF promoter and enhances cell viability in combination with mutant, but not wild-type, ß-catenin. Together, our study reveals the alteration of WNT, hedgehog, histone methyltransferase and now N-CoR pathways across medulloblastomas and within specific subtypes of this disease, and nominates the RNA helicase DDX3X as a component of pathogenic ß-catenin signalling in medulloblastoma.

Accurate Estimation of Fungal Diversity and Abundance through Improved Lineage-Specific Primers Optimized for Illumina Amplicon Sequencing.

While high-throughput sequencing methods are revolutionizing fungal ecology, recovering accurate estimates of species richness and abundance has proven elusive. We sought to design internal transcribed spacer (ITS) primers and an Illumina protocol that would maximize coverage of the kingdom Fungi while minimizing nontarget eukaryotes. We inspected alignments of the 5.8S and large subunit (LSU) ribosomal genes and evaluated potential primers using PrimerProspector. We tested the resulting primers using tiered-abundance mock communities and five previously characterized soil samples. We recovered operational taxonomic units (OTUs) belonging to all 8 members in both mock communities, despite DNA abundances spanning 3 orders of magnitude. The expected and observed read counts were strongly correlated (r = 0.94 to 0.97). However, several taxa were consistently over- or underrepresented, likely due to variation in rRNA gene copy numbers. The Illumina data resulted in clustering of soil samples identical to that obtained with Sanger sequence clone library data using different primers. Furthermore, the two methods produced distance matrices with a Mantel correlation of 0.92. Nonfungal sequences comprised less than 0.5% of the soil data set, with most attributable to vascular plants. Our results suggest that high-throughput methods can produce fairly accurate estimates of fungal abundances in complex communities. Further improvements might be achieved through corrections for rRNA copy number and utilization of standardized mock communities. IMPORTANCE: Fungi play numerous important roles in the environment. Improvements in sequencing methods are providing revolutionary insights into fungal biodiversity, yet accurate estimates of the number of fungal species (i.e., richness) and their relative abundances in an environmental sample (e.g., soil, roots, water, etc.) remain difficult to obtain. We present improved methods for high-throughput Illumina sequencing of the species-diagnostic fungal ribosomal marker gene that improve the accuracy of richness and abundance estimates. The improvements include new PCR primers and library preparation, validation using a known mock community, and bioinformatic parameter tuning.

Fine-mapping classical HLA variation associated with durable host control of HIV-1 infection in African Americans.

A small proportion of human immunodeficiency virus-1 (HIV-1) infected individuals, termed HIV-1 controllers, suppress viral replication to very low levels in the absence of therapy. Genetic investigations of this phenotype have strongly implicated variation in the class I major histocompatibility complex (MHC) region as key to HIV-1 control. We collected sequence-based classical class I HLA genotypes at 4-digit resolution in HIV-1-infected African American controllers and progressors (n = 1107), and tested them for association with host control using genome-wide single nucleotide polymorphism data to account for population structure. Several classical alleles at HLA-B were associated with host control, including B*57:03 [odds ratio (OR) = 5.1; P= 3.4 × 10(-18)] and B*81:01 (OR = 4.8; P= 1.3 × 10(-9)). Analysis of variable amino acid positions demonstrates that HLA-B position 97 is the most significant association with host control in African Americans (omnibus P = 1.2 × 10(-21)) and explains the signal of several HLA-B alleles, including B*57:03. Within HLA-B, we also identified independent effects at position 116 (omnibus P= 2.8 × 10(-15)) in the canonical F pocket, position 63 in the B pocket (P= 1.5 × 10(-3)) and the non-pocket position 245 (P= 8.8 × 10(-10)), which is thought to influence CD8-binding kinetics. Adjusting for these HLA-B effects, there is evidence for residual association in the MHC region. These results underscore the key role of HLA-B in affecting HIV-1 replication, likely through the molecular interaction between HLA-B and viral peptides presented by infected cells, and suggest that sites outside the peptide-binding pocket also influence HIV-1 control.

Whole genome deep sequencing of HIV-1 reveals the impact of early minor variants upon immune recognition during acute infection.

Deep sequencing technologies have the potential to transform the study of highly variable viral pathogens by providing a rapid and cost-effective approach to sensitively characterize rapidly evolving viral quasispecies. Here, we report on a high-throughput whole HIV-1 genome deep sequencing platform that combines 454 pyrosequencing with novel assembly and variant detection algorithms. In one subject we combined these genetic data with detailed immunological analyses to comprehensively evaluate viral evolution and immune escape during the acute phase of HIV-1 infection. The majority of early, low frequency mutations represented viral adaptation to host CD8+ T cell responses, evidence of strong immune selection pressure occurring during the early decline from peak viremia. CD8+ T cell responses capable of recognizing these low frequency escape variants coincided with the selection and evolution of more effective secondary HLA-anchor escape mutations. Frequent, and in some cases rapid, reversion of transmitted mutations was also observed across the viral genome. When located within restricted CD8 epitopes these low frequency reverting mutations were sufficient to prime de novo responses to these epitopes, again illustrating the capacity of the immune response to recognize and respond to low frequency variants. More importantly, rapid viral escape from the most immunodominant CD8+ T cell responses coincided with plateauing of the initial viral load decline in this subject, suggestive of a potential link between maintenance of effective, dominant CD8 responses and the degree of early viremia reduction. We conclude that the early control of HIV-1 replication by immunodominant CD8+ T cell responses may be substantially influenced by rapid, low frequency viral adaptations not detected by conventional sequencing approaches, which warrants further investigation. These data support the critical need for vaccine-induced CD8+ T cell responses to target more highly constrained regions of the virus in order to ensure the maintenance of immunodominant CD8 responses and the sustained decline of early viremia.

Whole genome pyrosequencing of rare hepatitis C virus genotypes enhances subtype classification and identification of naturally occurring drug resistance variants.

BACKGROUND: Infection with hepatitis C virus (HCV) is a burgeoning worldwide public health problem, with 170 million infected individuals and an estimated 20 million deaths in the coming decades. While 6 main genotypes generally distinguish the global geographic diversity of HCV, a multitude of closely related subtypes within these genotypes are poorly defined and may influence clinical outcome and treatment options. Unfortunately, the paucity of genetic data from many of these subtypes makes time-consuming primer walking the limiting step for sequencing understudied subtypes. METHODS: Here we combined long-range polymerase chain reaction amplification with pyrosequencing for a rapid approach to generate the complete viral coding region of 31 samples representing poorly defined HCV subtypes. RESULTS: Phylogenetic classification based on full genome sequences validated previously identified HCV subtypes, identified a recombinant sequence, and identified a new distinct subtype of genotype 4. Unlike conventional sequencing methods, use of deep sequencing also facilitated characterization of minor drug resistance variants within these uncommon or, in some cases, previously uncharacterized HCV subtypes. CONCLUSIONS: These data aid in the classification of uncommon HCV subtypes while also providing a high-resolution view of viral diversity within infected patients, which may be relevant to the development of therapeutic regimens to minimize drug resistance.

Assay Validation of Cell-Free DNA Shallow Whole-Genome Sequencing to Determine Tumor Fraction in Advanced Cancers.

Blood-based liquid biopsy is increasingly used in clinical care of patients with cancer, and fraction of tumor-derived DNA in circulation (tumor fraction; TFx) has demonstrated clinical validity across multiple cancer types. To determine TFx, shallow whole-genome sequencing of cell-free DNA (cfDNA) can be performed from a single blood sample, using an established computational pipeline (ichorCNA), without prior knowledge of tumor mutations, in a highly cost-effective manner. We describe assay validation of this approach to facilitate broad clinical application, including evaluation of assay sensitivity, precision, repeatability, reproducibility, pre-analytic factors, and DNA quality/quantity. Sensitivity to detect TFx of 3% (lower limit of detection) was 97.2% to 100% at 1× and 0.1× mean sequencing depth, respectively. Precision was demonstrated on distinct sequencing instruments (HiSeqX and NovaSeq) with no observable differences. The assay achieved prespecified 95% agreement of TFx across replicates of the same specimen (repeatability) and duplicate samples in different batches (reproducibility). Comparison of samples collected in EDTA and Streck tubes from single venipuncture in 23 patients demonstrated that EDTA or Streck tubes were comparable if processed within 8 hours. On the basis of a range of DNA inputs (1 to 50 ng), 20 ng cfDNA is the preferred input, with 5 ng minimum acceptable. Overall, this shallow whole-genome sequencing of cfDNA and ichorCNA approach offers sensitive, precise, and reproducible quantitation of TFx, facilitating assay application in clinical cancer care.

Selection, optimization and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse US populations.

Polygenic risk scores (PRSs) have improved in predictive performance, but several challenges remain to be addressed before PRSs can be implemented in the clinic, including reduced predictive performance of PRSs in diverse populations, and the interpretation and communication of genetic results to both providers and patients. To address these challenges, the National Human Genome Research Institute-funded Electronic Medical Records and Genomics (eMERGE) Network has developed a framework and pipeline for return of a PRS-based genome-informed risk assessment to 25,000 diverse adults and children as part of a clinical study. From an initial list of 23 conditions, ten were selected for implementation based on PRS performance, medical actionability and potential clinical utility, including cardiometabolic diseases and cancer. Standardized metrics were considered in the selection process, with additional consideration given to strength of evidence in African and Hispanic populations. We then developed a pipeline for clinical PRS implementation (score transfer to a clinical laboratory, validation and verification of score performance), and used genetic ancestry to calibrate PRS mean and variance, utilizing genetically diverse data from 13,475 participants of the All of Us Research Program cohort to train and test model parameters. Finally, we created a framework for regulatory compliance and developed a PRS clinical report for return to providers and for inclusion in an additional genome-informed risk assessment. The initial experience from eMERGE can inform the approach needed to implement PRS-based testing in diverse clinical settings.

A blended genome and exome sequencing method captures genetic variation in an unbiased, high-quality, and cost-effective manner.

We deployed the Blended Genome Exome (BGE), a DNA library blending approach that generates low pass whole genome (1-4× mean depth) and deep whole exome (30-40× mean depth) data in a single sequencing run. This technology is cost-effective, empowers most genomic discoveries possible with deep whole genome sequencing, and provides an unbiased method to capture the diversity of common SNP variation across the globe. To evaluate this new technology at scale, we applied BGE to sequence >53,000 samples from the Populations Underrepresented in Mental Illness Associations Studies (PUMAS) Project, which included participants across African, African American, and Latin American populations. We evaluated the accuracy of BGE imputed genotypes against raw genotype calls from the Illumina Global Screening Array. All PUMAS cohorts had R 2 concordance ≥95% among SNPs with MAF≥1%, and never fell below ≥90% R 2 for SNPs with MAF<1%. Furthermore, concordance rates among local ancestries within two recently admixed cohorts were consistent among SNPs with MAF≥1%, with only minor deviations in SNPs with MAF<1%. We also benchmarked the discovery capacity of BGE to access protein-coding copy number variants (CNVs) against deep whole genome data, finding that deletions and duplications spanning at least 3 exons had a positive predicted value of ~90%. Our results demonstrate BGE scalability and efficacy in capturing SNPs, indels, and CNVs in the human genome at 28% of the cost of deep whole-genome sequencing. BGE is poised to enhance access to genomic testing and empower genomic discoveries, particularly in underrepresented populations.

Genome-wide patterns of intrahuman dengue virus diversity reveal associations with viral phylogenetic clade and interhost diversity.

Analogous to observations in RNA viruses such as human immunodeficiency virus, genetic variation associated with intrahost dengue virus (DENV) populations has been postulated to influence viral fitness and disease pathogenesis. Previous attempts to investigate intrahost genetic variation in DENV characterized only a few viral genes or a limited number of full-length genomes. We developed a whole-genome amplification approach coupled with deep sequencing to capture intrahost diversity across the entire coding region of DENV-2. Using this approach, we sequenced DENV-2 genomes from the serum of 22 Nicaraguan individuals with secondary DENV infection and captured ∼75% of the DENV genome in each sample (range, 40 to 98%). We identified and quantified variants using a highly sensitive and specific method and determined that the extent of diversity was considerably lower than previous estimates. Significant differences in intrahost diversity were detected between genes and also between antigenically distinct domains of the Envelope gene. Interestingly, a strong association was discerned between the extent of intrahost diversity in a few genes and viral clade identity. Additionally, the abundance of viral variants within a host, as well as the impact of viral mutations on amino acid encoding and predicted protein function, determined whether intrahost variants were observed at the interhost level in circulating Nicaraguan DENV-2 populations, strongly suggestive of purifying selection across transmission events. Our data illustrate the value of high-coverage genome-wide analysis of intrahost diversity for high-resolution mapping of the relationship between intrahost diversity and clinical, epidemiological, and virological parameters of viral infection.

High-resolution analysis of intrahost genetic diversity in dengue virus serotype 1 infection identifies mixed infections.

Little is known about the rate at which genetic variation is generated within intrahost populations of dengue virus (DENV) and what implications this diversity has for dengue pathogenesis, disease severity, and host immunity. Previous studies of intrahost DENV variation have used a low frequency of sampling and/or experimental methods that do not fully account for errors generated through amplification and sequencing of viral RNAs. We investigated the extent and pattern of genetic diversity in sequence data in domain III (DIII) of the envelope (E) gene in serial plasma samples (n = 49) taken from 17 patients infected with DENV type 1 (DENV-1), totaling some 8,458 clones. Statistically rigorous approaches were employed to account for artifactual variants resulting from amplification and sequencing, which we suggest have played a major role in previous studies of intrahost genetic variation. Accordingly, nucleotide sequence diversities of viral populations were very low, with conservative estimates of the average levels of genetic diversity ranging from 0 to 0.0013. Despite such sequence conservation, we observed clear evidence for mixed infection, with the presence of multiple phylogenetically distinct lineages present within the same host, while the presence of stop codon mutations in some samples suggests the action of complementation. In contrast to some previous studies we observed no relationship between the extent and pattern of DENV-1 genetic diversity and disease severity, immune status, or level of viremia.

Endemic dengue associated with the co-circulation of multiple viral lineages and localized density-dependent transmission.

Dengue is one of the most important infectious diseases of humans and has spread throughout much of the tropical and subtropical world. Despite this widespread dispersal, the determinants of dengue transmission in endemic populations are not well understood, although essential for virus control. To address this issue we performed a phylogeographic analysis of 751 complete genome sequences of dengue 1 virus (DENV-1) sampled from both rural (Dong Thap) and urban (Ho Chi Minh City) populations in southern Viet Nam during the period 2003-2008. We show that DENV-1 in Viet Nam exhibits strong spatial clustering, with likely importation from Cambodia on multiple occasions. Notably, multiple lineages of DENV-1 co-circulated in Ho Chi Minh City. That these lineages emerged at approximately the same time and dispersed over similar spatial regions suggests that they are of broadly equivalent fitness. We also observed an important relationship between the density of the human host population and the dispersion rate of dengue, such that DENV-1 tends to move from urban to rural populations, and that densely populated regions within Ho Chi Minh City act as major transmission foci. Despite these fluid dynamics, the dispersion rates of DENV-1 are relatively low, particularly in Ho Chi Minh City where the virus moves less than an average of 20 km/year. These low rates suggest a major role for mosquito-mediated dispersal, such that DENV-1 does not need to move great distances to infect a new host when there are abundant susceptibles, and imply that control measures should be directed toward the most densely populated urban environments.

Highly sensitive and specific detection of rare variants in mixed viral populations from massively parallel sequence data.

Viruses diversify over time within hosts, often undercutting the effectiveness of host defenses and therapeutic interventions. To design successful vaccines and therapeutics, it is critical to better understand viral diversification, including comprehensively characterizing the genetic variants in viral intra-host populations and modeling changes from transmission through the course of infection. Massively parallel sequencing technologies can overcome the cost constraints of older sequencing methods and obtain the high sequence coverage needed to detect rare genetic variants (< 1%) within an infected host, and to assay variants without prior knowledge. Critical to interpreting deep sequence data sets is the ability to distinguish biological variants from process errors with high sensitivity and specificity. To address this challenge, we describe V-Phaser, an algorithm able to recognize rare biological variants in mixed populations. V-Phaser uses covariation (i.e. phasing) between observed variants to increase sensitivity and an expectation maximization algorithm that iteratively recalibrates base quality scores to increase specificity. Overall, V-Phaser achieved > 97% sensitivity and > 97% specificity on control read sets. On data derived from a patient after four years of HIV-1 infection, V-Phaser detected 2,015 variants across the -10 kb genome, including 603 rare variants (< 1% frequency) detected only using phase information. V-Phaser identified variants at frequencies down to 0.2%, comparable to the detection threshold of allele-specific PCR, a method that requires prior knowledge of the variants. The high sensitivity and specificity of V-Phaser enables identifying and tracking changes in low frequency variants in mixed populations such as RNA viruses.