Error rates, PCR recombination, and sampling depth in HIV-1 whole genome deep sequencing

COVID-19 diagnosis on the basis of nanobiosensors' prompt interactivity: A holistic review

The fast spread and severe consequences of novel coronavirus disease 2019 (COVID-19) have once again underscored the critical necessity of early detection of viral infections. Several serology-based techniques, including as point-of-care assays and high-throughput enzyme immunoassays that support the diagnosis of COVID-19 are utilized in the detection and identification of coronaviruses. A rapid, precise, simple, affordable, and adaptable diagnostic tool is required for controlling COVID-19 as well as for outbreak management, since the calculation and monitoring of viral loads are crucial for predicting the infection stage and recovery time. Nowadays, the most popular method for diagnosing COVID-19 is reverse transcription polymerase chain reaction (RT-PCR) testing, and chest computed tomography (CT) scans are also used to determine the disease's phases. This is all because of the fact that RT-PCR method caries with itself a number of downsides comprising of being immovable, expensive, and laborious. RT-PCR has not well proven to be capable of detection on the very early infection stages. Nanomaterial-based diagnostics, together with traditional clinical procedures, have a lot of promise against COVID-19. It is worthy of attention that nanotechnology has the mainstay capacity for purposes of developing even more modern stratagems fighting COVID-19 by means of focusing on state-of-the-art diagnostics. What we have centered on in this review, is bringing out even more efficient detection techniques whereby nanobiosensors are employed so that we might obstruct any further development and spreading of SARS-CoV-2.

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

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

Elevated HIV Viral Load is Associated with Higher Recombination Rate In Vivo

HIV's exceptionally high recombination rate drives its intrahost diversification, enabling immune escape and multidrug resistance within people living with HIV. While we know that HIV's recombination rate varies by genomic position, we have little understanding of how recombination varies throughout infection or between individuals as a function of the rate of cellular coinfection. We hypothesize that denser intrahost populations may have higher rates of coinfection and therefore recombination. To test this hypothesis, we develop a new approach (recombination analysis via time series linkage decay or RATS-LD) to quantify recombination using autocorrelation of linkage between mutations across time points. We validate RATS-LD on simulated data under short read sequencing conditions and then apply it to longitudinal, high-throughput intrahost viral sequencing data, stratifying populations by viral load (a proxy for density). Among sampled viral populations with the lowest viral loads (<26,800 copies/mL), we estimate a recombination rate of 1.5×10-5 events/bp/generation (95% CI: 7×10-6 to 2.9×10-5), similar to existing estimates. However, among samples with the highest viral loads (>82,000 copies/mL), our median estimate is approximately 6 times higher. In addition to co-varying across individuals, we also find that recombination rate and viral load are associated within single individuals across different time points. Our findings suggest that rather than acting as a constant, uniform force, recombination can vary dynamically and drastically across intrahost viral populations and within them over time. More broadly, we hypothesize that this phenomenon may affect other facultatively asexual populations where spatial co-localization varies.

Elevated HIV viral load is associated with higher recombination rate in vivo

HIV's exceptionally high recombination rate drives its intra-host diversification, enabling immune escape and multi-drug resistance within people living with HIV. While we know that HIV's recombination rate varies by genomic position, we have little understanding of how recombination varies throughout infection or between individuals as a function of the rate of cellular coinfection. We hypothesize that denser intra-host populations may have higher rates of coinfection and therefore recombination. To test this hypothesis, we develop a new approach (Recombination Analysis via Time Series Linkage Decay, or RATS-LD) to quantify recombination using autocorrelation of linkage between mutations across time points. We validate RATS-LD on simulated data under short read sequencing conditions and then apply it to longitudinal, high-throughput intra-host viral sequencing data, stratifying populations by viral load (a proxy for density). Among sampled viral populations with the lowest viral loads (< 26,800 copies/mL), we estimate a recombination rate of 1.5 × 10-5 events/bp/generation (95% CI: 7 × 10-6 - 2.9 × 10-5), similar to existing estimates. However, among samples with the highest viral loads (> 82,000 copies/mL), our median estimate is approximately 6 times higher. In addition to co-varying across individuals, we also find that recombination rate and viral load are associated within single individuals across different time points. Our findings suggest that rather than acting as a constant, uniform force, recombination can vary dynamically and drastically across intra-host viral populations and within them over time. More broadly, we hypothesize that this phenomenon may affect other facultatively asexual populations where spatial co-localization varies.

Accurate estimation of molecular counts from amplicon sequence data with unique molecular identifiers

MOTIVATION

Amplicon sequencing is widely applied to explore heterogeneity and rare variants in genetic populations. Resolving true biological variants and quantifying their abundance is crucial for downstream analyses, but measured abundances are distorted by stochasticity and bias in amplification, plus errors during polymerase chain reaction (PCR) and sequencing. One solution attaches unique molecular identifiers (UMIs) to sample sequences before amplification. Counting UMIs instead of sequences provides unbiased estimates of abundance. While modern methods improve over naïve counting by UMI identity, most do not account for UMI reuse or collision, and they do not adequately model PCR and sequencing errors in the UMIs and sample sequences.

RESULTS

We introduce Deduplication and Abundance estimation with UMIs (DAUMI), a probabilistic framework to detect true biological amplicon sequences and accurately estimate their deduplicated abundance. DAUMI recognizes UMI collision, even on highly similar sequences, and detects and corrects most PCR and sequencing errors in the UMI and sampled sequences. DAUMI performs better on simulated and real data compared to other UMI-aware clustering methods.

AVAILABILITY AND IMPLEMENTATION

Source code is available at https://github.com/DormanLab/AmpliCI.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Discordance between HIV-1 Population in Plasma at Rebound after Structured Treatment Interruption and Archived Provirus Population in Peripheral Blood Mononuclear Cells

Antiretroviral therapy (ART) can sustain the suppression of plasma viremia to below detection levels. Infected individuals undergoing a treatment interruption exhibit rapid viral rebound in plasma viremia which is fueled by cellular reservoirs such as CD4+ T cells, myeloid cells, and potentially uncharacterized cellular sources. Interrogating the populations of viruses found during analytical treatment interruption (ATI) can give insights into the biologically competent reservoirs that persist under effective ART as well as the nature of the cellular reservoirs that enable viral persistence under ART. We interrogated plasma viremia from four rare cases of individuals undergoing sequential ATIs. We performed next-generation sequencing (NGS) on cell-associated viral DNA and cell-free virus to understand the interrelationship between sequential ATIs as well as the relationship between viral genomes in circulating peripheral blood mononuclear cells (PBMCs) and RNA from rebound plasma. We observed population differences between viral populations recrudescing at sequential ATIs as well as divergence between viral sequences in plasma and those in PBMCs. This indicated that viruses in PBMCs were not a major source of post-ATI viremia and highlights the role of anatomic reservoirs in post-ATI viremia and viral persistence. IMPORTANCE Even with effective ART, HIV-1 persists at undetectable levels and rebounds in individuals who stop treatment. Cellular and anatomical reservoirs ignite viral rebound upon treatment interruption, remaining one of the key obstacles for HIV-1 cure. To further examine HIV-1 persistence, a better understanding of the distinct populations that fuel viral rebound is necessary to identify and target reservoirs and the eradication of HIV-1. This study investigates the populations of viruses found from proviral genomes from PBMCs and plasma at rebound from a unique cohort of individuals who underwent multiple rounds of treatment interruption. Using NGS, we characterized the subtypes of viral sequences and found divergence in viral populations between plasma and PBMCs at each rebound, suggesting that distinct viral populations appear at each treatment interruption.

HIV DNA Sequencing to Detect Archived Antiretroviral Drug Resistance

INTRODUCTION

Proviral HIV DNA integrated within CD4 T-cells maintains an archive of viral variants that replicate during the course of the infection, including variants with reduced drug susceptibility. We considered studies that investigated archived drug resistance, with a focus on virologically suppressed patients and highlighted interpretative caveats and gaps in knowledge.

RESULTS

Either Sanger or deep sequencing can be used to investigate resistance-associated mutations (RAMs) in HIV DNA recovered from peripheral blood. Neither technique is free of limitations. Furthermore, evidence regarding the establishment, maintenance, expression and clinical significance of archived drug-resistant variants is conflicting. This in part reflects the complexity of the HIV proviral landscape and its dynamics during therapy. Clinically, detection of RAMs in cellular HIV DNA has a variable impact on treatment outcomes, modulated by the drugs affected, treatment duration and additional determinants of virological failure, including those leading to suboptimal drug exposure.

CONCLUSIONS

Sequencing cellular HIV DNA can provide helpful complementary information in treatment-experienced patients with suppressed plasma HIV RNA who require a change of regimen. However, care should be taken when interpreting the results. Presence of RAMs is not necessarily a barrier to treatment success. Conversely, even the most sensitive sequencing techniques will fail to provide a comprehensive view of the HIV DNA archive. To inform treatment decisions appropriately, the overall clinical and treatment history of a patient must always be considered alongside the results of resistance testing. Prospective controlled studies are needed to validate the utility of drug resistance testing using cellular HIV DNA.

Droplet-microfluidics-assisted sequencing of HIV proviruses and their integration sites in cells from people on antiretroviral therapy

The human immunodeficiency virus (HIV) integrates its genome in that of infected cells and may enter an inactive state of reversible latency that cannot be targeted using antiretroviral therapy. The resulting HIV DNA is termed a provirus. Sequencing individual proviruses with the adjacent human cellular junctions may elucidate mechanisms of infected cell persistence in humans. Here, we introduce a high throughput microfluidic assay where droplet-based whole genome amplification of the HIV DNA in its native context is followed by a polymerase chain reaction to tag droplets containing proviruses for sequencing, resulting in the assembly of full-length viral genomes connected to their contiguous HIV-human DNA junctions, regardless of the 150 million-fold higher amount of human DNA present in the background. We analyzed infected cells from patients with HIV receiving suppressive antiretroviral therapy, resulting in the detection and sequencing of paired proviral genomes and integration sites, 90% of which weren’t recovered by commonly used nested PCR methods. The sequencing of individual proviral genomes with their integration sites could improve the genetic analysis of persistent HIV-infected cell reservoirs.

Plasma-Derived HIV-1 Virions Contain Considerable Levels of Defective Genomes

Genetically-characterizing full-length HIV-1 RNA is critical for identifying genetically-intact genomes and for comparing these RNA genomes to proviral DNA. We have developed a method for sequencing plasma-derived RNA using long-range sequencing (PRLS assay; ∼8.3 kb from gag to the 3′ end or ∼5 kb from integrase to the 3′ end). We employed the gag-3′ PRLS assay to sequence HIV-1 RNA genomes from ART-naive participants during acute/early infection (n = 6) or chronic infection (n = 2). On average, only 65% of plasma-derived genomes were genetically-intact. Defects were found in all genomic regions but were concentrated in env and pol. We compared these genomes to near-full-length proviral sequences from paired peripheral blood mononuclear cell (PBMC) samples for the acute/early group and found that near-identical (>99.98% identical) sequences were identified only during acute infection. For three participants who initiated therapy during acute infection, we used the int-3′ PRLS assay to sequence plasma-derived genomes from an analytical treatment interruption and identified 100% identical genomes between pretherapy and rebound time points. The PRLS assay provides a new level of sensitivity for understanding the genetic composition of plasma-derived HIV-1 RNA from viremic individuals either pretherapy or after treatment interruption, which will be invaluable in assessing possible HIV-1 curative strategies.

IMPORTANCE We developed novel plasma-derived RNA using long-range sequencing assays (PRLS assay; 8.3 kb, gag-3′, and 5.0 kb, int-3′). Employing the gag-3′ PRLS assay, we found that 26% to 51% of plasma-derived genomes are genetically-defective, largely as a result of frameshift mutations and deletions. These genetic defects were concentrated in the env region compared to gag and pol, likely a reflection of viral immune escape in env during untreated HIV-1 infection. Employing the int-3′ PRLS assay, we found that analytical treatment interruption (ATI) plasma-derived sequences were identical and genetically-intact. Several sequences from the ATI plasma samples were identical to viral sequences from pretherapy plasma and PBMC samples, indicating that HIV-1 reservoirs established prior to therapy contribute to viral rebound during an ATI. Therefore, near-full-length sequencing of HIV-1 particles is required to gain an accurate picture of the genetic landscape of plasma HIV-1 virions in studies of HIV-1 replication and persistence.

Chemistry and Bioinformatics Considerations in Using Next-Generation Sequencing Technologies to Inferring HIV Proviral DNA Genome-Intactness

HIV persists via integration of the viral DNA into the human genome. The HIV DNA pool within an infected individual is a complex population that comprises both intact and defective viral genomes, each with a distinct integration site, in addition to a unique repertoire of viral quasi-species. Obtaining an accurate profile of the viral DNA pool is critical to understanding viral persistence and resolving interhost differences. Recent advances in next-generation deep sequencing (NGS) technologies have enabled the development of two sequencing assays to capture viral near-full- genome sequences at single molecule resolution (FLIP-seq) or to co-capture full-length viral genome sequences in conjunction with its associated viral integration site (MIP-seq). This commentary aims to provide an overview on both FLIP-seq and MIP-seq, discuss their strengths and limitations, and outline specific chemistry and bioinformatics concerns when using these assays to study HIV persistence.

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

Monitoring the spread of SARS-CoV-2 and reconstructing transmission chains has become a major public health focus for many governments around the world. The modest mutation rate and rapid transmission of SARS-CoV-2 prevents the reconstruction of transmission chains from consensus genome sequences, but within-host genetic diversity could theoretically help identify close contacts. Here we describe the patterns of within-host diversity in 1181 SARS-CoV-2 samples sequenced to high depth in duplicate. 95.1% of samples show within-host mutations at detectable allele frequencies. Analyses of the mutational spectra revealed strong strand asymmetries suggestive of damage or RNA editing of the plus strand, rather than replication errors, dominating the accumulation of mutations during the SARS-CoV-2 pandemic. Within- and between-host diversity show strong purifying selection, particularly against nonsense mutations. Recurrent within-host mutations, many of which coincide with known phylogenetic homoplasies, display a spectrum and patterns of purifying selection more suggestive of mutational hotspots than recombination or convergent evolution. While allele frequencies suggest that most samples result from infection by a single lineage, we identify multiple putative examples of co-infection. Integrating these results into an epidemiological inference framework, we find that while sharing of within-host variants between samples could help the reconstruction of transmission chains, mutational hotspots and rare cases of superinfection can confound these analyses.

MrHAMER yields highly accurate single molecule viral sequences enabling analysis of intra-host evolution

Technical challenges remain in the sequencing of RNA viruses due to their high intra-host diversity. This bottleneck is particularly pronounced when interrogating long-range co-evolved genetic interactions given the read-length limitations of next-generation sequencing platforms. This has hampered the direct observation of these genetic interactions that code for protein-protein interfaces with relevance in both drug and vaccine development. Here we overcome these technical limitations by developing a nanopore-based long-range viral sequencing pipeline that yields accurate single molecule sequences of circulating virions from clinical samples. We demonstrate its utility in observing the evolution of individual HIV Gag-Pol genomes in response to antiviral pressure. Our pipeline, called Multi-read Hairpin Mediated Error-correction Reaction (MrHAMER), yields >1000s of viral genomes per sample at 99.9% accuracy, maintains the original proportion of sequenced virions present in a complex mixture, and allows the detection of rare viral genomes with their associated mutations present at <1% frequency. This method facilitates scalable investigation of genetic correlates of resistance to both antiviral therapy and immune pressure and enables the identification of novel host-viral and viral-viral interfaces that can be modulated for therapeutic benefit.

Characterization of HIV-1 recombinant and subtype B near full-length genome among men who have sex with men in South Korea

In Korea, subtype B is the predominant variant of HIV-1, but full genome sequencing and analysis of its viral variants are lacking. We performed near full-length genome (NFLG) sequencing and phylogenetic and recombination analyses of fifty plasma samples from HIV-positive men who have sex with men (MSM) from a Korea HIV/AIDS cohort study. Viral genomes were amplified and the near-full-length sequences were determined using next-generation sequencing (NGS) and Sanger sequencing. We focused on the HIV-1 subtype classification and identification of HIV recombinants. Twelve HIV-1 NFLGs were determined: ten were subtyped as pure HIV-1 subtype B and two recombinant strains as a common subtype CRF07_BC, and a novel subtype CRF43_02G recombined with CRF02_AG again, or a new CRF02_AG and subtype G recombinant. For the ten NFLGs determined by NGS, “the novel recombinant emerged at approximately 2003 and the other nine subtype B about 2004 or 2005”. This is the first report analyzing HIV-1 NFLG, including recombinants and clinical characteristics, by subtype among MSM in Korea. Our results provide novel insights for understanding the recombinants in the HIV-1 epidemic in Korea.

Applying next-generation sequencing to unravel the mutational landscape in viral quasispecies

Next-generation sequencing (NGS) has revolutionized the scale and depth of biomedical sciences. Because of its unique ability for the detection of sub-clonal variants within genetically diverse populations, NGS has been successfully applied to analyze and quantify the exceptionally-high diversity within viral quasispecies, and many low-frequency drug- or vaccine-resistant mutations of therapeutic importance have been discovered. Although many works have intensively discussed the latest NGS approaches and applications in general, none of them has focused on applying NGS in viral quasispecies studies, mostly due to the limited ability of current NGS technologies to accurately detect and quantify rare viral variants. Here, we summarize several error-correction strategies that have been developed to enhance the detection accuracy of minority variants. We also discuss critical considerations for preparing a sequencing library from viral RNAs and for analyzing NGS data to unravel the mutational landscape.

Measurement error and variant-calling in deep Illumina sequencing of HIV

MOTIVATION

Next-generation deep sequencing of viral genomes, particularly on the Illumina platform, is increasingly applied in HIV research. Yet, there is no standard protocol or method used by the research community to account for measurement errors that arise during sample preparation and sequencing. Correctly calling high and low-frequency variants while controlling for erroneous variants is an important precursor to downstream interpretation, such as studying the emergence of HIV drug-resistance mutations, which in turn has clinical applications and can improve patient care.

RESULTS

We developed a new variant-calling pipeline, hivmmer, for Illumina sequences from HIV viral genomes. First, we validated hivmmer by comparing it to other variant-calling pipelines on real HIV plasmid datasets. We found that hivmmer achieves a lower rate of erroneous variants, and that all methods agree on the frequency of correctly called variants. Next, we compared the methods on an HIV plasmid dataset that was sequenced using Primer ID, an amplicon-tagging protocol, which is designed to reduce errors and amplification bias during library preparation. We show that the Primer ID consensus exhibits fewer erroneous variants compared to the variant-calling pipelines, and that hivmmer more closely approaches this low error rate compared to the other pipelines. The frequency estimates from the Primer ID consensus do not differ significantly from those of the variant-calling pipelines.

AVAILABILITY AND IMPLEMENTATION

hivmmer is freely available for non-commercial use from https://github.com/kantorlab/hivmmer.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

High-throughput sequencing (HTS) for the analysis of viral populations

The development of High-Throughput Sequencing (HTS) technologies is having a major impact on the genomic analysis of viral populations. Current HTS platforms can capture nucleic acid variation across millions of genes for both selected amplicons and full viral genomes. HTS has already facilitated the discovery of new viruses, hinted new taxonomic classifications and provided a deeper and broader understanding of their diversity, population and genetic structure. Hence, HTS has already replaced standard Sanger sequencing in basic and applied research fields, but the next step is its implementation as a routine technology for the analysis of viruses in clinical settings. The most likely application of this implementation will be the analysis of viral genomics, because the huge population sizes, high mutation rates and very fast replacement of viral populations have demonstrated the limited information obtained with Sanger technology. In this review, we describe new technologies and provide guidelines for the high-throughput sequencing and genetic and evolutionary analyses of viral populations and metaviromes, including software applications. With the development of new HTS technologies, new and refurbished molecular and bioinformatic tools are also constantly being developed to process and integrate HTS data. These allow assembling viral genomes and inferring viral population diversity and dynamics. Finally, we also present several applications of these approaches to the analysis of viral clinical samples including transmission clusters and outbreak characterization.

Prevalence and clinical impact of minority resistant variants in patients failing an integrase inhibitor-based regimen by ultra-deep sequencing

Background

Integrase strand transfer inhibitors (INSTIs) are recommended by international guidelines as first-line therapy in antiretroviral-naive and -experienced HIV-1-infected patients.

Objectives

This study aimed at evaluating the prevalence at failure of INSTI-resistant variants and the impact of baseline minority resistant variants (MiRVs) on the virological response to an INSTI-based regimen.

Methods

Samples at failure of 134 patients failing a raltegravir-containing (n = 65), an elvitegravir-containing (n = 20) or a dolutegravir-containing (n = 49) regimen were sequenced by Sanger sequencing and ultra-deep sequencing (UDS). Baseline samples of patients with virological failure (VF) (n = 34) and of those with virological success (VS) (n = 31) under INSTI treatment were sequenced by UDS. Data were analysed using the SmartGene platform, and resistance was interpreted according to the ANRS algorithm version 27.

Results

At failure, the prevalence of at least one INSTI-resistant variant was 39.6% by Sanger sequencing and 57.5% by UDS, changing the interpretation of resistance in 17/134 (13%) patients. Among 53 patients harbouring at least one resistance mutation detected by both techniques, the most dominant INSTI resistance mutations were N155H (45%), Q148H/K/R (23%), T97A (19%) and Y143C (11%). There was no difference in prevalence of baseline MiRVs between patients with VF and those with VS. MiRVs found at baseline in patients with VF were not detected at failure either in majority or minority mutations.

Conclusions

UDS is more sensitive than Sanger sequencing at detecting INSTI MiRVs at treatment failure. The presence of MiRVs at failure could be important to the decision to switch to other INSTIs. However, there was no association between the presence of baseline MiRVs and the response to INSTI-based therapies in our study.

Intra- and interpatient evolution of enterovirus D68 analyzed by whole-genome deep sequencing

Worldwide outbreaks of enterovirus D68 (EV-D68) in 2014 and 2016 have caused serious respiratory and neurological disease. To investigate diversity, spread, and evolution of EV-D68 we performed near full-length deep sequencing in fifty-four samples obtained in Sweden during the 2014 and 2016 outbreaks. In most samples, intrapatient variability was low and dominated by rare synonymous variants, but three patients showed evidence of dual infections with distinct EV-D68 variants from the same subclade. Interpatient evolution showed a very strong temporal signal, with an evolutionary rate of 0.0039 ± 0.0001 substitutions per site and year. Phylogenetic trees reconstructed from the sequences suggest that EV-D68 was introduced into Stockholm several times during the 2016 outbreak. Putative neutralization targets in the BC and DE loops of the VP1 protein were slightly more diverse within-host and tended to undergo more frequent substitution than other genomic regions. However, evolution in these loops did not appear to have been driven the emergence of the 2016 B3-subclade directly from the 2014 B1-subclade. Instead, the most recent ancestor of both clades was dated to 2009. The study provides a comprehensive description of the intra- and interpatient evolution of EV-D68, including the first report of intrapatient diversity and dual infections. The new data along with publicly available EV-D68 sequences are included in an interactive phylodynamic analysis on nextstrain.org/enterovirus/d68 to facilitate timely EV-D68 tracking in the future.

PCR Amplification Strategies Towards Full-length HIV-1 Genome Sequencing

The advent of next-generation sequencing has enabled greater resolution of viral diversity and improved feasibility of full viral genome sequencing allowing routine HIV-1 full genome sequencing in both research and diagnostic settings. Regardless of the sequencing platform selected, successful PCR amplification of the HIV-1 genome is essential for sequencing template preparation. As such, full HIV-1 genome amplification is a crucial step in dictating the successful and reliable sequencing downstream. Here we reviewed existing PCR protocols leading to HIV-1 full genome sequencing. In addition to the discussion on basic considerations on relevant PCR design, the advantages as well as the pitfalls of the published protocols were reviewed.

VirGenA: a reference-based assembler for variable viral genomes

Characterization of the within-host genetic diversity of viral pathogens is required for selection of effective treatment of some important viral infections, e.g. HIV, HBV and HCV. Despite the technical ability of detection, there are conflicting data regarding the clinical significance of low-frequency variants, partially because of the difficulty of their distinguishing from experimental artifacts. The issue of cross-contamination is relevant for all highly sensitive techniques, including deep sequencing: even trace contamination leads to a significant increase of false positives in identified SNVs. Determination of infections by multiple genotypes of some viruses, the incidence of which can be considerable, especially in risk groups, is also clinically significant in some cases. We developed a new viral reference-guided assembler, VirGenA, that can separate mixtures of strains of different intraspecies genetic groups (genotypes, subtypes, clades, etc.) and assemble a separate consensus sequence for each group in a mixture. It produced long assemblies for mixture components of extremely low frequencies (<1%) allowing detection of cross-contamination of samples by divergent genotypes. We tested VirGenA on both clinical and simulated data. On both types of data, VirGenA shows better or similar results than the existing de novo assemblers. Cross-platform implementation (including source code) is freely available at https://github.com/gFedonin/VirGenA/releases.

An amplicon-based sequencing framework for accurately measuring intrahost virus diversity using PrimalSeq and iVar

How viruses evolve within hosts can dictate infection outcomes; however, reconstructing this process is challenging. We evaluate our multiplexed amplicon approach, PrimalSeq, to demonstrate how virus concentration, sequencing coverage, primer mismatches, and replicates influence the accuracy of measuring intrahost virus diversity. We develop an experimental protocol and computational tool, iVar, for using PrimalSeq to measure virus diversity using Illumina and compare the results to Oxford Nanopore sequencing. We demonstrate the utility of PrimalSeq by measuring Zika and West Nile virus diversity from varied sample types and show that the accumulation of genetic diversity is influenced by experimental and biological systems.

Measurements of intrahost viral diversity require an unbiased diversity metric

Viruses exist within hosts at large population sizes and are subject to high rates of mutation. As such, viral populations exhibit considerable sequence diversity. A variety of summary statistics have been developed which describe, in a single number, the extent of diversity in a viral population; such measurements allow the diversities of different populations to be compared, and the effect of evolutionary forces on a population to be assessed. Here we highlight statistical artefacts underlying some common measures of sequence diversity, whereby variation in the depth of genome sequencing may substantially affect the extent of diversity measured in a viral population, making comparisons of population diversity invalid. Specifically, naive estimation of sequence entropy provides a systematically biased metric, a lower read depth being expected to produce a lower estimate of diversity. The number of polymorphic loci per kilobase of genome is more unpredictably affected by read depth, giving potentially flawed results at lower sequencing depths. We show that the nucleotide diversity statistic π provides an unbiased estimate of diversity in the sense that the expected value of the statistic is equal to the correct value of the property being measured. Our results are of importance for studies interpreting genome sequence data; we describe how diversity may be assessed in viral populations in a fair and unbiased manner.

A novel framework for inferring parameters of transmission from viral sequence data

Transmission between hosts is a critical part of the viral lifecycle. Recent studies of viral transmission have used genome sequence data to evaluate the number of particles transmitted between hosts, and the role of selection as it operates during the transmission process. However, the interpretation of sequence data describing transmission events is a challenging task. We here present a novel and comprehensive framework for using short-read sequence data to understand viral transmission events, designed for influenza virus, but adaptable to other viral species. Our approach solves multiple shortcomings of previous methods for this purpose; for example, we consider transmission as an event involving whole viruses, rather than sets of independent alleles. We demonstrate how selection during transmission and noisy sequence data may each affect naive inferences of the population bottleneck, accounting for these in our framework so as to achieve a correct inference. We identify circumstances in which selection for increased viral transmission may or may not be identified from data. Applying our method to experimental data in which transmission occurs in the presence of strong selection, we show that our framework grants a more quantitative insight into transmission events than previous approaches, inferring the bottleneck in a manner that accounts for selection, both for within-host virulence, and for inherent viral transmissibility. Our work provides new opportunities for studying transmission processes in influenza, and by extension, in other infectious diseases.

Within-patient mutation frequencies reveal fitness costs of CpG dinucleotides and drastic amino acid changes in HIV

HIV has a high mutation rate, which contributes to its ability to evolve quickly. However, we know little about the fitness costs of individual HIV mutations in vivo, their distribution and the different factors shaping the viral fitness landscape. We calculated the mean frequency of transition mutations at 870 sites of the pol gene in 160 patients, allowing us to determine the cost of these mutations. As expected, we found high costs for non-synonymous and nonsense mutations as compared to synonymous mutations. In addition, we found that non-synonymous mutations that lead to drastic amino acid changes are twice as costly as those that do not and mutations that create new CpG dinucleotides are also twice as costly as those that do not. We also found that G→A and C→T mutations are more costly than A→G mutations. We anticipate that our new in vivo frequency-based approach will provide insights into the fitness landscape and evolvability of not only HIV, but a variety of microbes.

A Survey of Virus Recombination Uncovers Canonical Features of Artificial Chimeras Generated During Deep Sequencing Library Preparation

Chimeric reads can be generated by in vitro recombination during the preparation of high-throughput sequencing libraries. Our attempt to detect biological recombination between the genomes of dengue virus (DENV; +ssRNA genome) and its mosquito host using the Illumina Nextera sequencing library preparation kit revealed that most, if not all, detected host-virus chimeras were artificial. Indeed, these chimeras were not more frequent than with control RNA from another species (a pillbug), which was never in contact with DENV RNA prior to the library preparation. The proportion of chimera types merely reflected those of the three species among sequencing reads. Chimeras were frequently characterized by the presence of 1-20 bp microhomology between recombining fragments. Within-species chimeras mostly involved fragments in opposite orientations and located less than 100 bp from each other in the parental genome. We found similar features in published datasets using two other viruses: Ebola virus (EBOV; -ssRNA genome) and a herpesvirus (dsDNA genome), both produced with the Illumina Nextera protocol. These canonical features suggest that artificial chimeras are generated by intra-molecular template switching of the DNA polymerase during the PCR step of the Nextera protocol. Finally, a published Illumina dataset using the Flock House virus (FHV; +ssRNA genome) generated with a protocol preventing artificial recombination revealed the presence of 1-10 bp microhomology motifs in FHV-FHV chimeras, but very few recombining fragments were in opposite orientations. Our analysis uncovered sequence features characterizing recombination breakpoints in short-read sequencing datasets, which can be helpful to evaluate the presence and extent of artificial recombination.

Within-Host Evolution of Human Influenza Virus

The rapid global evolution of influenza virus begins with mutations that arise de novo in individual infections, but little is known about how evolution occurs within hosts. We review recent progress in understanding how and why influenza viruses evolve within human hosts. Advances in deep sequencing make it possible to measure within-host genetic diversity in both acute and chronic influenza infections. Factors like antigenic selection, antiviral treatment, tissue specificity, spatial structure, and multiplicity of infection may affect how influenza viruses evolve within human hosts. Studies of within-host evolution can contribute to our understanding of the evolutionary and epidemiological factors that shape influenza virus's global evolution.

HIV evolution and diversity in ART-treated patients

Characterizing HIV genetic diversity and evolution during antiretroviral therapy (ART) provides insights into the mechanisms that maintain the viral reservoir during ART. This review describes common methods used to obtain and analyze intra-patient HIV sequence data, the accumulation of diversity prior to ART and how it is affected by suppressive ART, the debate on viral replication and evolution in the presence of ART, HIV compartmentalization across various tissues, and mechanisms for the emergence of drug resistance. It also describes how CD4+ T cells that were likely infected with latent proviruses prior to initiating treatment can proliferate before and during ART, providing a renewable source of infected cells despite therapy. Some expanded cell clones carry intact and replication-competent proviruses with a small fraction of the clonal siblings being transcriptionally active and a source for residual viremia on ART. Such cells may also be the source for viral rebound after interrupting ART. The identical viral sequences observed for many years in both the plasma and infected cells of patients on long-term ART are likely due to the proliferation of infected cells both prior to and during treatment. Studies on HIV diversity may reveal targets that can be exploited in efforts to eradicate or control the infection without ART.

On the effective depth of viral sequence data

Genome sequence data are of great value in describing evolutionary processes in viral populations. However, in such studies, the extent to which data accurately describes the viral population is a matter of importance. Multiple factors may influence the accuracy of a dataset, including the quantity and nature of the sample collected, and the subsequent steps in viral processing. To investigate this phenomenon, we sequenced replica datasets spanning a range of viruses, and in which the point at which samples were split was different in each case, from a dataset in which independent samples were collected from a single patient to another in which all processing steps up to sequencing were applied to a single sample before splitting the sample and sequencing each replicate. We conclude that neither a high read depth nor a high template number in a sample guarantee the precision of a dataset. Measures of consistency calculated from within a single biological sample may also be insufficient; distortion of the composition of a population by the experimental procedure or genuine within-host diversity between samples may each affect the results. Where it is possible, data from replicate samples should be collected to validate the consistency of short-read sequence data.

Estimating time of HIV-1 infection from next-generation sequence diversity

Estimating the time since infection (TI) in newly diagnosed HIV-1 patients is challenging, but important to understand the epidemiology of the infection. Here we explore the utility of virus diversity estimated by next-generation sequencing (NGS) as novel biomarker by using a recent genome-wide longitudinal dataset obtained from 11 untreated HIV-1-infected patients with known dates of infection. The results were validated on a second dataset from 31 patients. Virus diversity increased linearly with time, particularly at 3rd codon positions, with little inter-patient variation. The precision of the TI estimate improved with increasing sequencing depth, showing that diversity in NGS data yields superior estimates to the number of ambiguous sites in Sanger sequences, which is one of the alternative biomarkers. The full advantage of deep NGS was utilized with continuous diversity measures such as average pairwise distance or site entropy, rather than the fraction of polymorphic sites. The precision depended on the genomic region and codon position and was highest when 3rd codon positions in the entire pol gene were used. For these data, TI estimates had a mean absolute error of around 1 year. The error increased only slightly from around 0.6 years at a TI of 6 months to around 1.1 years at 6 years. Our results show that virus diversity determined by NGS can be used to estimate time since HIV-1 infection many years after the infection, in contrast to most alternative biomarkers. We provide the regression coefficients as well as web tool for TI estimation.

HIV-1 establishes a chronic infection, which may last for many years before the infected person is diagnosed. The resulting uncertainty in the date of infection leads to difficulties in estimating the number of infected but undiagnosed persons as well as the number of new infections, which is necessary for developing appropriate public health policies and interventions. Such estimates would be much easier if the time since HIV-1 infection for newly diagnosed cases could be accurately estimated. Three types of biomarkers have been shown to contain information about the time since HIV-1 infection, but unfortunately, they only distinguish between recent and long-term infections (concentration of HIV-1-specific antibodies) or are imprecise (immune status as measured by levels of CD4+ T-lymphocytes and viral sequence diversity measured by polymorphisms in Sanger sequences). In this paper, we show that recent advances in sequencing technologies, i.e. the development of next generation sequencing, enable significantly more precise determination of the time since HIV-1 infection, even many years after the infection event. This is a significant advance which could translate into more effective HIV-1 prevention.

Mutation and recombination in pathogen evolution: Relevance, methods and controversies

Mutation and recombination drive the evolution of most pathogens by generating the genetic variants upon which selection operates. Those variants can, for example, confer resistance to host immune systems and drug therapies or lead to epidemic outbreaks. Given their importance, diverse evolutionary studies have investigated the abundance and consequences of mutation and recombination in pathogen populations. However, some controversies persist regarding the contribution of each evolutionary force to the development of particular phenotypic observations (e.g., drug resistance). In this study, we revise the importance of mutation and recombination in the evolution of pathogens at both intra-host and inter-host levels. We also describe state-of-the-art analytical methodologies to detect and quantify these two evolutionary forces, including biases that are often ignored in evolutionary studies. Finally, we present some of our former studies involving pathogenic taxa where mutation and recombination played crucial roles in the recovery of pathogenic fitness, the generation of interspecific genetic diversity, or the design of centralized vaccines. This review also illustrates several common controversies and pitfalls in the analysis and in the evaluation and interpretation of mutation and recombination outcomes.

Recent advances in understanding HIV evolution

The human immunodeficiency virus (HIV) evolves rapidly owing to the combined activity of error-prone reverse transcriptase, recombination, and short generation times, leading to extensive viral diversity both within and between hosts. This diversity is a major contributing factor in the failure of the immune system to eradicate the virus and has important implications for the development of suitable drugs and vaccines to combat infection. This review will discuss the recent technological advances that have shed light on HIV evolution and will summarise emerging concepts in this field.