Within-Host Viral Diversity: A Window into Viral Evolution

A binary trait model reveals the fitness effects of HIV-1 escape from T cell responses

Natural selection often acts on multiple traits simultaneously. For example, the virus HIV-1 faces pressure to evade host immunity while also preserving replicative fitness. While past work has studied selection during HIV-1 evolution, as in other examples where selection acts on multiple traits, it is challenging to quantitatively separate different contributions to fitness. This task is made more difficult because a single mutation can affect both immune escape and replication. Here, we develop an evolutionary model that disentangles the effects of escaping CD8+ T cell-mediated immunity, which we model as a binary trait, from other contributions to fitness. After validation in simulations, we applied this model to study within-host HIV-1 evolution in a clinical dataset. We observed strong selection for immune escape, sometimes greatly exceeding past estimates, especially early in infection. Conservative estimates suggest that roughly half of HIV-1 fitness gains during the first months to years of infection can be attributed to T cell escape. Our approach is not limited to HIV-1 or viruses and could be adapted to study the evolution of quantitative traits in other contexts.

Comparative genetic analysis of pathogenic and attenuated strains of Junín virus

Junín virus (JUNV) is a mammarenavirus that causes Argentine hemorrhagic fever (AHF). Mammarenaviruses are RNA viruses with an ambisense, bi-segmented genome containing four genes encoding the glycoproteins (GPC), the nucleoprotein (NP), the RNA polymerase (L) and the matrix protein (Z). Several JUNV strains with different pathogenicity have already been fully sequenced. We performed a comprehensive and comparative analysis of their genetic differences and phylogeny, focusing on the synonymous codon usage patterns of the JUNV proteins. We found a nucleotide identity of > 95% between strains, with significant differences between all genes for GC% and Z and L genes for GC3%. Analysis of relative synonymous codon usage showed that codons AGA and AGG of the amino acid arginine were overrepresented, while CGC, CGA and CGG of arginine, GCG of alanine, ACG of threonine, CCG of proline and TCG of serine were underrepresented in the GPC, NP and L genes. A weak codon usage bias was observed, with GPC having a significantly higher effective number of codons. Moreover, selection could explain at least 83% of the observed bias. Analysis of the codon adaptation index revealed a better adaptation for B cells and kidney and a lower one for endothelial cells. We also observed a possible reassortment event between the MC2 and Romero strains. This work provides a new perspective on the genetic diversity of JUNV strains, which may contribute to the development of new approaches for future research into the evolutionary model, origin and host adaptation of JUNV causing AHF.

Dispersal of influenza virus populations within the respiratory tract shapes their evolutionary potential

Viral infections are characterized by dispersal from an initial site to secondary locations within the host. How the resultant spatial heterogeneity shapes within-host genetic diversity and viral evolutionary pathways is poorly understood. Here, we show that virus dispersal within and between the nasal cavity and trachea maintains diversity and is therefore conducive to adaptive evolution, whereas dispersal to the lungs gives rise to population heterogeneity. We infected ferrets either intranasally or by aerosol with a barcoded influenza A/California/07/2009 (H1N1) virus. At 1, 2, or 4 days postinfection, dispersal was assessed by collecting 52 samples from throughout the respiratory tract of each animal. Irrespective of inoculation route, barcode compositions across the nasal turbinates and trachea were similar and highly diverse, revealing little constraint on the establishment of infection in the nasal cavity and descent through the trachea. Conversely, infection of the lungs produced genetically distinct viral populations. Lung populations were pauci-clonal, suggesting that each seeded location received relatively few viral genotypes. While aerosol inoculation gave distinct populations at every lung site sampled, within-host dispersal after intranasal inoculation produced larger patches, indicative of local expansion following seeding of the lungs. Throughout the respiratory tract, barcode diversity declined over time, but new diversity was generated through mutation. De novo variants were often unique to a given location, indicating that localized replication following dispersal resulted in population divergence. In summary, dispersal within the respiratory tract operates differently between regions and contributes to the potential for viral evolution to proceed independently in multiple within-host subpopulations.

Impact of Viral Co-Detection on the Within-Host Viral Diversity of Influenza Patients

Numerous studies have documented the evidence of virus-virus interactions at the population, host, and cellular levels. However, the impact of these interactions on the within-host diversity of influenza viral populations remains unexplored. Our study identified 13 respiratory viral pathogens from the nasopharyngeal swab samples (NPSs) of influenza-like-illness (ILI) patients during the 2012/13 influenza season using multiplex RT-PCR. Subsequent next-generation sequencing (NGS) of RT-PCR-confirmed influenza A infections revealed all samples as subtype A/H3N2. Out of the 2305 samples tested, 538 (23.3%) were positive for the influenza A virus (IAV), while rhinovirus (RV) and adenoviruses (Adv) were detected in 264 (11.5%) and 44 (1.9%) samples, respectively. Among these, the co-detection of more than one virus was observed in ninety-six samples, and five samples showed co-detections involving more than two viruses. The most frequent viral co-detection was IAV-RV, identified in 48 out of the 96 co-detection cases. Of the total samples, 150 were processed for whole-genome sequencing (WGS), and 132 met the criteria for intra-host single-nucleotide variant (iSNV) calling. Across the genome, 397 unique iSNVs were identified, with most samples containing fewer than five iSNVs at frequencies below 10%. Seven samples had no detectable iSNVs. Notably, the majority of iSNVs (86%) were unique and rarely shared across samples. We conducted a negative binomial regression analysis to examine factors associated with the number of iSNVs detected within hosts. Two age groups-elderly individuals (>64 years old) and school-aged children (6-18 years old)-were significantly associated with higher iSNV counts, with incidence rate ratios (IRR) of 1.80 (95% confidence interval [CI]: 1.09-3.06) and 1.38 (95% CI: 1.01-1.90), respectively. Our findings suggest a minor or negligible contribution of these viral co-detections to the evolution of influenza viruses. However, the data available in this study may not be exhaustive, warranting further, more in-depth investigations to conclusively determine the impact of virus-virus interactions on influenza virus genetic diversity.

Phylogenetic inferences reveal multiple intra- and interhost genetic diversity among bat rabies viruses circulating in northeastern Brazil

BACKGROUND

Rabies, a lethal viral zoonotic disease, remains a significant global public health concern. In northeastern Brazil, in particular, its epidemiology is complex and dynamic, characterized by the presence of several reservoirs associated with human rabies infection.

METHODS

This study, conducted from June 2022 to July 2023, was part of a passive epidemiological surveillance initiative under Brazil's National Rabies Surveillance Program. It investigated the presence of Rhabdovirus (RhabV) in 356 postmortem chiropteran brain samples using three diagnostic techniques for rabies and conducted an evolutionary study on both pan-RhabV- and pan-LYSSAV-positive PCR samples. The samples were collected from 20 bat species and different locations in the State of Ceará, an endemic region for the rabies virus (RABV). Rabies-positive samples were further explored through Bayesian, genetic distance mapping and recombination analyses.

RESULTS

From a total of 356 samples collected, 43 (12.07%) were positive for direct immunofluorescence (DIF) and 40 (11.23%) for mouse intracerebral inoculation (MIT) tests. Among the positive results, 40 samples were confirmed by both DIF and MIT, while 13 (3.65%) had inconclusive results for one or both techniques. Molecular assays identified 38 rabies-positive samples (10.67%). Members of the Molossidae and Phyllostomidae families had the highest prevalence, highlighting the role of insectivorous and frugivorous bats in the cycle and dynamics of rabies transmission. Phylogenetic reconstructions revealed three distinct and well-supported clusters and clades, indicating the cocirculation of different RABV lineages in the region and shedding light on both intra- and interhost diversity. We also demonstrated genetic distance among the RABV clusters and inferred that their common ancestor originated in Europe, later diversifying across continents. No recombination breakpoints were identified.

CONCLUSIONS

This study highlights the dynamic nature of RABV evolution within individual bat hosts, contributing to the understanding of the genetic diversity of RABV variants found in several bat species in northeastern Brazil. This study provides crucial insights into viral transmission dynamics within and between different host species and is essential for designing effective rabies control and prevention strategies tailored to endemic regions.

Virus Evolution in Prolonged Infections of Immunocompromised Individuals

BACKGROUND

Many viruses can cause persistent infection and/or viral shedding in immunocompromised hosts. This is a well-described occurrence not only with SARS-CoV-2 but for many other viruses as well. Understanding how viruses evolve and mutate in these patients and the global impact of this phenomenon is critical as the immunocompromised population expands.

CONTENT

In this review, we provide an overview of populations at risk for prolonged viral shedding, clinical manifestations of persistent viral infection, and methods of assessing viral evolution. We then review the literature on viral evolution in immunocompromised patients across an array of RNA viruses, including SARS-CoV-2, norovirus, influenza, and poliovirus, and discuss the global implications of persistent viral infections in these hosts.

SUMMARY

There is significant evidence for accelerated viral evolution and accumulation of mutations in antigenic sites in immunocompromised hosts across many viral pathogens. However, the implications of this phenomenon are not clear; while there are rare reports of transmission of these variants, they have not clearly been shown to predict disease outbreaks or have significant global relevance. Emerging methods including wastewater monitoring may provide a more sophisticated understanding of the impact of variants that evolve in immunocompromised hosts on the wider host population.

DiMA: sequence diversity dynamics analyser for viruses

Sequence diversity is one of the major challenges in the design of diagnostic, prophylactic, and therapeutic interventions against viruses. DiMA is a novel tool that is big data-ready and designed to facilitate the dissection of sequence diversity dynamics for viruses. DiMA stands out from other diversity analysis tools by offering various unique features. DiMA provides a quantitative overview of sequence (DNA/RNA/protein) diversity by use of Shannon's entropy corrected for size bias, applied via a user-defined k-mer sliding window to an input alignment file, and each k-mer position is dissected to various diversity motifs. The motifs are defined based on the probability of distinct sequences at a given k-mer alignment position, whereby an index is the predominant sequence, while all the others are (total) variants to the index. The total variants are sub-classified into the major (most common) variant, minor variants (occurring more than once and of incidence lower than the major), and the unique (singleton) variants. DiMA allows user-defined, sequence metadata enrichment for analyses of the motifs. The application of DiMA was demonstrated for the alignment data of the relatively conserved Spike protein (2,106,985 sequences) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the relatively highly diverse pol gene (2637) of the human immunodeficiency virus-1 (HIV-1). The tool is publicly available as a web server (https://dima.bezmialem.edu.tr), as a Python library (via PyPi) and as a command line client (via GitHub).

Apollo: A comprehensive GPU-powered within-host simulator for viral evolution and infection dynamics across population, tissue, and cell

Modern sequencing instruments bring unprecedented opportunity to study within-host viral evolution in conjunction with viral transmissions between hosts. However, no computational simulators are available to assist the characterization of within-host dynamics. This limits our ability to interpret epidemiological predictions incorporating within-host evolution and to validate computational inference tools. To fill this need we developed Apollo, a GPU-accelerated, out-of-core tool for within-host simulation of viral evolution and infection dynamics across population, tissue, and cellular levels. Apollo is scalable to hundreds of millions of viral genomes and can handle complex demographic and population genetic models. Apollo can replicate real within-host viral evolution; accurately recapturing observed viral sequences from an HIV cohort derived from initial population-genetic configurations. For practical applications, using Apollo-simulated viral genomes and transmission networks, we validated and uncovered the limitations of a widely used viral transmission inference tool.

A binary trait model reveals the fitness effects of HIV-1 escape from T cell responses

Natural selection often acts on multiple traits simultaneously. For example, the virus HIV-1 faces pressure to evade host immunity while also preserving replicative fitness. While past work has studied selection during HIV-1 evolution, as in other examples where selection acts on multiple traits, it is challenging to quantitatively separate different contributions to fitness. This task is made more difficult because a single mutation can affect both immune escape and replication. Here, we develop an evolutionary model that disentangles the effects of escaping CD8+T cell-mediated immunity, which we model as a binary trait, from other contributions to fitness. After validation in simulations, we applied this model to study within-host HIV-1 evolution in a clinical data set. We observed strong selection for immune escape, sometimes greatly exceeding past estimates, especially early in infection. Conservative estimates suggest that roughly half of HIV-1 fitness gains during the first months to years of infection can be attributed to T cell escape. Our approach is not limited to HIV-1 or viruses, and could be adapted to study the evolution of quantitative traits in other contexts.

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.

Embracing Complexity: What Novel Sequencing Methods Are Teaching Us About Herpesvirus Genomic Diversity

The arrival of novel sequencing technologies throughout the past two decades has led to a paradigm shift in our understanding of herpesvirus genomic diversity. Previously, herpesviruses were seen as a family of DNA viruses with low genomic diversity. However, a growing body of evidence now suggests that herpesviruses exist as dynamic populations that possess standing variation and evolve at much faster rates than previously assumed. In this review, we explore how strategies such as deep sequencing, long-read sequencing, and haplotype reconstruction are allowing scientists to dissect the genomic composition of herpesvirus populations. We also discuss the challenges that need to be addressed before a detailed picture of herpesvirus diversity can emerge.

Entourage: all-in-one sequence analysis software for genome assembly, virus detection, virus discovery, and intrasample variation profiling

BACKGROUND

Pan-virus detection, and virome investigation in general, can be challenging, mainly due to the lack of universally conserved genetic elements in viruses. Metagenomic next-generation sequencing can offer a promising solution to this problem by providing an unbiased overview of the microbial community, enabling detection of any viruses without prior target selection. However, a major challenge in utilising metagenomic next-generation sequencing for virome investigation is that data analysis can be highly complex, involving numerous data processing steps.

RESULTS

Here, we present Entourage to address this challenge. Entourage enables short-read sequence assembly, viral sequence search with or without reference virus targets using contig-based approaches, and intrasample sequence variation quantification. Several workflows are implemented in Entourage to facilitate end-to-end virus sequence detection analysis through a single command line, from read cleaning, sequence assembly, to virus sequence searching. The results generated are comprehensive, allowing for thorough quality control, reliability assessment, and interpretation. We illustrate Entourage's utility as a streamlined workflow for virus detection by employing it to comprehensively search for target virus sequences and beyond in raw sequence read data generated from HeLa cell culture samples spiked with viruses. Furthermore, we showcase its flexibility and performance on a real-world dataset by analysing a preassembled Tara Oceans dataset. Overall, our results show that Entourage performs well even with low virus sequencing depth in single digits, and it can be used to discover novel viruses effectively. Additionally, by using sequence data generated from a patient with chronic SARS-CoV-2 infection, we demonstrate Entourage's capability to quantify virus intrasample genetic variations, and generate publication-quality figures illustrating the results.

CONCLUSIONS

Entourage is an all-in-one, versatile, and streamlined bioinformatics software for virome investigation, developed with a focus on ease of use. Entourage is available at https://codeberg.org/CENMIG/Entourage under the MIT license.

Comparative analysis of multiple consensus genomes of the same strain of Marek's disease virus reveals intrastrain variation

Current strategies to understand the molecular basis of Marek's disease virus (MDV) virulence primarily consist of cataloging divergent nucleotides between strains with different phenotypes. However, most comparative genomic studies of MDV rely on previously published consensus genomes despite the confirmed existence of MDV strains as mixed viral populations. To assess the reliability of interstrain genomic comparisons relying on published consensus genomes of MDV, we obtained two additional consensus genomes of vaccine strain CVI988 (Rispens) and two additional consensus genomes of the very virulent strain Md5 by sequencing viral stocks and cultured field isolates. In conjunction with the published genomes of CVI988 and Md5, this allowed us to perform three-way comparisons between multiple consensus genomes of the same strain. We found that consensus genomes of CVI988 can vary in as many as 236 positions involving 13 open reading frames (ORFs). By contrast, we found that Md5 genomes varied only in 11 positions involving a single ORF. Notably, we were able to identify 3 single-nucleotide polymorphisms (SNPs) in the unique long region and 16 SNPs in the unique short (US) region of CVI988GenBank.BAC that were not present in either CVI988Pirbright.lab or CVI988USDA.PA.field. Recombination analyses of field strains previously described as natural recombinants of CVI988 yielded no evidence of crossover events in the US region when either CVI988Pirbright.lab or CVI988USDA.PA.field were used to represent CVI988 instead of CVI988GenBank.BAC. We were also able to confirm that both CVI988 and Md5 populations were mixed, exhibiting a total of 29 and 27 high-confidence minor variant positions, respectively. However, we did not find any evidence of minor variants in the positions corresponding to the 19 SNPs in the unique regions of CVI988GenBank.BAC. Taken together, our findings suggest that continued reliance on the same published consensus genome of CVI988 may have led to an overestimation of genomic divergence between CVI988 and virulent strains and that multiple consensus genomes per strain may be necessary to ensure the accuracy of interstrain genomic comparisons.

Within-host influenza viral diversity in the pediatric population as a function of age, vaccine, and health status

Seasonal influenza virus predominantly evolves through antigenic drift, marked by the accumulation of mutations at antigenic sites. Because of antigenic drift, influenza vaccines are frequently updated, though their efficacy may still be limited due to strain mismatches. Despite the high levels of viral diversity observed across populations, most human studies reveal limited intrahost diversity, leaving the origin of population-level viral diversity unclear. Previous studies show host characteristics, such as immunity, might affect within-host viral evolution. Here we investigate influenza A viral diversity in children aged between 6 months and 18 years. Influenza virus evolution in children is less well characterized than in adults, yet may be associated with higher levels of viral diversity given the lower level of pre-existing immunity and longer durations of infection in children. We obtained influenza isolates from banked influenza A-positive nasopharyngeal swabs collected at the Children's Hospital of Philadelphia during the 2017-18 influenza season. Using next-generation sequencing, we evaluated the population of influenza viruses present in each sample. We characterized within-host viral diversity using the number and frequency of intrahost single-nucleotide variants (iSNVs) detected in each sample. We related viral diversity to clinical metadata, including subjects' age, vaccination status, and comorbid conditions, as well as sample metadata such as virus strain and cycle threshold. Consistent with previous studies, most samples contained low levels of diversity with no clear association between the subjects' age, vaccine status, or health status. Further, there was no enrichment of iSNVs near known antigenic sites. Taken together, these findings are consistent with previous observations that the majority of intrahost influenza virus infection is characterized by low viral diversity without evidence of diversifying selection.

Improved detection of low-frequency within-host variants from deep sequencing: A case study with human papillomavirus

High-coverage sequencing allows the study of variants occurring at low frequencies within samples, but is susceptible to false-positives caused by sequencing error. Ion Torrent has a very low single nucleotide variant (SNV) error rate and has been employed for the majority of human papillomavirus (HPV) whole genome sequences. However, benchmarking of intrahost SNVs (iSNVs) has been challenging, partly due to limitations imposed by the HPV life cycle. We address this problem by deep sequencing three replicates for each of 31 samples of HPV type 18 (HPV18). Errors, defined as iSNVs observed in only one of three replicates, are dominated by C→T (G→A) changes, independently of trinucleotide context. True iSNVs, defined as those observed in all three replicates, instead show a more diverse SNV type distribution, with particularly elevated C→T rates in CCG context (CCG→CTG; CGG→CAG) and C→A rates in ACG context (ACG→AAG; CGT→CTT). Characterization of true iSNVs allowed us to develop two methods for detecting true variants: (1) VCFgenie, a dynamic binomial filtering tool which uses each variant's allele count and coverage instead of fixed frequency cut-offs; and (2) a machine learning binary classifier which trains eXtreme Gradient Boosting models on variant features such as quality and trinucleotide context. Each approach outperforms fixed-cut-off filtering of iSNVs, and performance is enhanced when both are used together. Our results provide improved methods for identifying true iSNVs in within-host applications across sequencing platforms, specifically using HPV18 as a case study.

Comparative Analysis of Multiple Consensus Genomes of the Same Strain of Marek's Disease Virus Reveals Intrastrain Variation

Current strategies to understand the molecular basis of Marek's disease virus (MDV) virulence primarily consist of cataloguing divergent nucleotides between strains with different phenotypes. However, each MDV strain is typically represented by a single consensus genome despite the confirmed existence of mixed viral populations. To assess the reliability of single-consensus interstrain genomic comparisons, we obtained two additional consensus genomes of vaccine strain CVI988 (Rispens) and two additional consensus genomes of the very virulent strain Md5 by sequencing viral stocks and cultured field isolates. In conjunction with the published genomes of CVI988 and Md5, this allowed us to perform 3-way comparisons between consensus genomes of the same strain. We found that consensus genomes of CVI988 can vary in as many as 236 positions involving 13 open reading frames (ORFs). In contrast, we found that Md5 genomes varied only in 11 positions involving a single ORF. Phylogenomic analyses showed all three Md5 consensus genomes clustered closely together, while also showing that CVI988 GenBank.BAC diverged from CVI988 Pirbright.lab and CVI988 USDA.PA.field . Comparison of CVI988 consensus genomes revealed 19 SNPs in the unique regions of CVI988 GenBank.BAC that were not present in either CVI988 Pirbright.lab or CVI988 USDA.PA.field . Finally, we evaluated the genomic heterogeneity of CVI988 and Md5 populations by identifying positions with >2% read support for alternative alleles in two ultra-deeply sequenced samples. We were able to confirm that both populations of CVI988 and Md5 were mixed, exhibiting a total of 29 and 27 high-confidence minor variant positions, respectively. We did not find any evidence of minor variants in the positions corresponding to the 19 SNPs in the unique regions of CVI988 GenBank.BAC . Taken together, our findings confirm that consensus genomes of the same strain of MDV can vary and suggest that multiple consensus genomes per strain are needed in order to maximize the accuracy of interstrain genomic comparisons.

Optimal entropic properties of SARS-CoV-2 RNA sequences

The reaction of the scientific community against the COVID-19 pandemic has generated a huge (approx. 106 entries) dataset of genome sequences collected worldwide and spanning a relatively short time window. These unprecedented conditions together with the certain identification of the reference viral genome sequence allow for an original statistical study of mutations in the virus genome. In this paper, we compute the Shannon entropy of every sequence in the dataset as well as the relative entropy and the mutual information between the reference sequence and the mutated ones. These functions, originally developed in information theory, measure the information content of a sequence and allows us to study the random character of mutation mechanism in terms of its entropy and information gain or loss. We show that this approach allows us to set in new format known features of the SARS-CoV-2 mutation mechanism like the CT bias, but also to discover new optimal entropic properties of the mutation process in the sense that the virus mutation mechanism track closely theoretically computable lower bounds for the entropy decrease and the information transfer.

Flexible changes to the Heliothis virescens ascovirus 3h (HvAV-3h) virion components affect pathogenicity against different host larvae species

IMPORTANCE

Different pathogenic processes of a virus in different hosts are related to the host individual differences, which makes the virus undergoes different survival pressures. Here, we found that the virions of an insect virus, Heliothis virescens ascovirus 3h (HvAV-3h), had different protein composition when they were purified from different host larval species. These "adaptive changes" of the virions were analyzed in detail in this study, which mainly included the differences of the protein composition of virions and the differences in affinity between virions and different host proteins. The results of this study revealed the flexible changes of viruses to help themselves adapt to different hosts. Also, these interesting findings can provide new insights to improve our understanding of virus adaptability and virulence differentiation caused by the adaptation process.

A Herpes Simplex Virus 1 DNA Polymerase Multidrug Resistance Mutation Identified in a Patient With Immunodeficiency and Confirmed by Gene Editing

BACKGROUND

Herpes simplex virus 1 can cause severe infections in individuals who are immunocompromised. In these patients, emergence of drug resistance mutations causes difficulties in infection management.

METHODS

Seventeen herpes simplex virus 1 isolates were obtained from orofacial/anogenital lesions in a patient with leaky severe combined immunodeficiency over 7 years, before and after stem cell transplantation. Spatial/temporal evolution of drug resistance was characterized genotypically-with Sanger and next-generation sequencing of viral thymidine kinase (TK) and DNA polymerase (DP)-and phenotypically. CRISPR/Cas9 was used to introduce the novel DP Q727R mutation, and dual infection-competition assays were performed to assess viral fitness.

RESULTS

Isolates had identical genetic backgrounds, suggesting that orofacial/anogenital infections derived from the same virus lineage. Eleven isolates proved heterogeneous TK virus populations by next-generation sequencing, undetectable by Sanger sequencing. Thirteen isolates were acyclovir resistant due to TK mutations, and the Q727R isolate additionally exhibited foscarnet/adefovir resistance. Recombinant Q727R mutant virus showed multidrug resistance and increased fitness under antiviral pressure.

CONCLUSIONS

Long-term follow-up of a patient with severe combined immunodeficiency revealed virus evolution and frequent reactivation of wild-type and TK mutant strains, mostly as heterogeneous populations. The DP Q727R resistance phenotype was confirmed with CRISPR/Cas9, a useful tool to validate novel drug resistance mutations.

A Simulation Framework for Modeling the Within-Patient Evolutionary Dynamics of SARS-CoV-2

The global impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to considerable interest in detecting novel beneficial mutations and other genomic changes that may signal the development of variants of concern (VOCs). The ability to accurately detect these changes within individual patient samples is important in enabling early detection of VOCs. Such genomic scans for rarely acting positive selection are best performed via comparison of empirical data with simulated data wherein commonly acting evolutionary factors, including mutation and recombination, reproductive and infection dynamics, and purifying and background selection, can be carefully accounted for and parameterized. Although there has been work to quantify these factors in SARS-CoV-2, they have yet to be integrated into a baseline model describing intrahost evolutionary dynamics. To construct such a baseline model, we develop a simulation framework that enables one to establish expectations for underlying levels and patterns of patient-level variation. By varying eight key parameters, we evaluated 12,096 different model-parameter combinations and compared them with existing empirical data. Of these, 592 models (∼5%) were plausible based on the resulting mean expected number of segregating variants. These plausible models shared several commonalities shedding light on intrahost SARS-CoV-2 evolutionary dynamics: severe infection bottlenecks, low levels of reproductive skew, and a distribution of fitness effects skewed toward strongly deleterious mutations. We also describe important areas of model uncertainty and highlight additional sequence data that may help to further refine a baseline model. This study lays the groundwork for the improved analysis of existing and future SARS-CoV-2 within-patient data.

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

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

A simulation framework for modeling the within-patient evolutionary dynamics of SARS-CoV-2

The global impact of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has led to considerable interest in detecting novel beneficial mutations and other genomic changes that may signal the development of variants of concern (VOCs). The ability to accurately detect these changes within individual patient samples is important in enabling early detection of VOCs. Such genomic scans for positive selection are best performed via comparison of empirical data to simulated data wherein evolutionary factors, including mutation and recombination rates, reproductive and infection dynamics, and purifying and background selection, can be carefully accounted for and parameterized. While there has been work to quantify these factors in SARS-CoV-2, they have yet to be integrated into a baseline model describing intra-host evolutionary dynamics. To construct such a baseline model, we develop a simulation framework that enables one to establish expectations for underlying levels and patterns of patient-level variation. By varying eight key parameters, we evaluated 12,096 different model-parameter combinations and compared them to existing empirical data. Of these, 592 models (~5%) were plausible based on the resulting mean expected number of segregating variants. These plausible models shared several commonalities shedding light on intra-host SARS-CoV-2 evolutionary dynamics: severe infection bottlenecks, low levels of reproductive skew, and a distribution of fitness effects skewed towards strongly deleterious mutations. We also describe important areas of model uncertainty and highlight additional sequence data that may help to further refine a baseline model. This study lays the groundwork for the improved analysis of existing and future SARS-CoV-2 within-patient data.

Identification and characterization of codon usage pattern and influencing factors in HFRS-causing hantaviruses

Hemorrhagic fever with renal syndrome (HFRS) is an acute viral zoonosis carried and transmitted by infected rodents through urine, droppings, or saliva. The etiology of HFRS is complex due to the involvement of viral factors and host immune and genetic factors which hinder the development of potential therapeutic solutions for HFRS. Hantaan virus (HTNV), Dobrava-Belgrade virus (DOBV), Seoul virus (SEOV), and Puumala virus (PUUV) are predominantly found in hantaviral species that cause HFRS in patients. Despite ongoing prevention and control efforts, HFRS remains a serious economic burden worldwide. Furthermore, recent studies reported that the hantavirus nucleocapsid protein is a multi-functional protein and plays a major role in the replication cycle of the hantavirus. However, the precise mechanism of the nucleoproteins in viral pathogenesis is not completely understood. In the framework of the current study, various in silico approaches were employed to identify the factors influencing the codon usage pattern of hantaviral nucleoproteins. Based on the relative synonymous codon usage (RSCU) values, a comparative analysis was performed between HFRS-causing hantavirus and their hosts, suggesting that HTNV, DOBV, SEOV, and PUUV, were inclined to evolve their codon usage patterns that were comparable to those of their hosts. The results indicated that most of the overrepresented codons had AU-endings, which revealed that mutational pressure is the major force shaping codon usage patterns. However, the influence of natural selection and geographical factors cannot be ignored on viral codon usage bias. Further analysis also demonstrated that HFRS causing hantaviruses adapted host-specific codon usage patterns to sustain successful replication and transmission chains within hosts. To our knowledge, no study to date reported the factors influencing the codon usage pattern within hantaviral nucleoproteins. Thus, the proposed computational scheme can help in understanding the underlying mechanism of codon usage patterns in HFRS-causing hantaviruses which lend a helping hand in designing effective anti-HFRS treatments in future. This study, although comprehensive, relies on in silico methods and thus necessitates experimental validation for more solid outcomes. Beyond the identified factors influencing viral behavior, there could be other yet undiscovered influences. These potential factors should be targets for further research to improve HFRS therapeutic strategies.

Physiological variations in hypovirus-infected wild and model long-term laboratory strains of Cryphonectria parasitica

Introduction

Forest ecosystems are highly threatened by the simultaneous effects of climate change and invasive pathogens. Chestnut blight, caused by the invasive phytopathogenic fungus Cryphonectria parasitica, has caused severe damage to European chestnut groves and catastrophic dieback of American chestnut in North America. Within Europe, the impacts of the fungus are widely mitigated through biological control that utilizes the RNA mycovirus: Cryphonectria hypovirus 1 (CHV1). Viral infections, similarly to abiotic factors, can cause oxidative stress in their hosts leading to physiological attrition through stimulating ROS (reactive oxygen species) and NOx production.

Methods

To fully understand the interactions leading to the biocontrol of chestnut blight, it is vital to determine oxidative stress damage arising during CHV1 infection, especially considering that other abiotic factors, like long-term cultivation of model fungal strains, can also impact oxidative stress. Our study compared CHV1-infected C. parasitica isolates from two Croatian wild populations with CHV1-infected model strains (EP713, Euro7 and CR23) that have experienced long-term laboratory cultivation.

Results and Discussion

We determined the level of oxidative stress in the samples by measuring stress enzymes' activity and oxidative stress biomarkers. Furthermore, for the wild populations, we studied the activity of fungal laccases, expression of the laccase gene lac1, and a possible effect of CHV1 intra-host diversity on the observed biochemical responses. Relative to the wild isolates, the long-term model strains had lower enzymatic activities of superoxide dismutase (SOD) and glutathione S-transferase (GST), and higher content of malondialdehyde (MDA) and total non-protein thiols. This indicated generally higher oxidative stress, likely arising from their decades-long history of subculturing and freeze-thaw cycles. When comparing the two wild populations, differences between them in stress resilience and levels of oxidative stress were also observed, as evident from the different MDA content. The intra-host genetic diversity of the CHV1 had no discernible effect on the stress levels of the virus-infected fungal cultures. Our research indicated that an important determinant modulating both lac1 expression and laccase enzyme activity is intrinsic to the fungus itself, possibly related to the vc type of the fungus, i.e., vegetative incompatibility genotype.

Human papillomavirus genomics: Understanding carcinogenicity

Human papillomavirus (HPV) causes virtually all cervical cancers and many cancers at other anatomical sites in both men and women. However, only 12 of 448 known HPV types are currently classified as carcinogens, and even the most carcinogenic type - HPV16 - only rarely leads to cancer. HPV is therefore necessary but insufficient for cervical cancer, with other contributing factors including host and viral genetics. Over the last decade, HPV whole genome sequencing has established that even fine-scale within-type HPV variation influences precancer/cancer risks, and that these risks vary by histology and host race/ethnicity. In this review, we place these findings in the context of the HPV life cycle and evolution at various levels of viral diversity: between-type, within-type, and within-host. We also discuss key concepts necessary for interpreting HPV genomic data, including features of the viral genome; events leading to carcinogenesis; the role of APOBEC3 in HPV infection and evolution; and methodologies that use deep (high-coverage) sequencing to characterize within-host variation, as opposed to relying on a single representative (consensus) sequence. Given the continued high burden of HPV-associated cancers, understanding HPV carcinogenicity remains important for better understanding, preventing, and treating cancers attributable to infection.

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

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

TRIAL REGISTRATION

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.

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

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

The Innovative Informatics Approaches of High-Throughput Technologies in Livestock: Spearheading the Sustainability and Resiliency of Agrigenomics Research

For more than a decade, next-generation sequencing (NGS) has been emerging as the mainstay of agrigenomics research. High-throughput technologies have made it feasible to facilitate research at the scale and cost required for using this data in livestock research. Scale frameworks of sequencing for agricultural and livestock improvement, management, and conservation are partly attributable to innovative informatics methodologies and advancements in sequencing practices. Genome-wide sequence-based investigations are often conducted worldwide, and several databases have been created to discover the connections between worldwide scientific accomplishments. Such studies are beginning to provide revolutionary insights into a new era of genomic prediction and selection capabilities of various domesticated livestock species. In this concise review, we provide selected examples of the current state of sequencing methods, many of which are already being used in animal genomic studies, and summarize the state of the positive attributes of genome-based research for cattle (Bos taurus), sheep (Ovis aries), pigs (Sus scrofa domesticus), horses (Equus caballus), chickens (Gallus gallus domesticus), and ducks (Anas platyrhyncos). This review also emphasizes the advantageous features of sequencing technologies in monitoring and detecting infectious zoonotic diseases. In the coming years, the continued advancement of sequencing technologies in livestock agrigenomics will significantly influence the sustained momentum toward regulatory approaches that encourage innovation to ensure continued access to a safe, abundant, and affordable food supplies for future generations.

A road map for in vivo evolution experiments with blood-borne parasitic microbes

Laboratory experiments in which blood-borne parasitic microbes evolve in their animal hosts offer an opportunity to study parasite evolution and adaptation in real time and under natural settings. The main challenge of these experiments is to establish a protocol that is both practical over multiple passages and accurately reflects natural transmission scenarios and mechanisms. We provide a guide to the steps that should be considered when designing such a protocol, and we demonstrate its use via a case study. We highlight the importance of choosing suitable ancestral genotypes, treatments, number of replicates per treatment, types of negative controls, dependent variables, covariates, and the timing of checkpoints for the experimental design. We also recommend specific preliminary experiments to determine effective methods for parasite quantification, transmission, and preservation. Although these methodological considerations are technical, they also often have conceptual implications. To this end, we encourage other researchers to design and conduct in vivo evolution experiments with blood-borne parasitic microbes, despite the challenges that the work entails.

RNA-Dependent RNA Polymerase of the Second Human Pegivirus Exhibits a High-Fidelity Feature

The virus-encoded RNA-dependent RNA polymerase (RdRp) is responsible for viral replication, and its fidelity is closely related to viral diversity, pathogenesis, virulence, and fitness. Hepatitis C virus (HCV) and the second human pegivirus (HPgV-2) belong to the family Flaviviridae and share some features, including similar viral genome structure. Unlike HCV, HPgV-2 preserves a highly conserved genome sequence and low intrahost variation. However, the underlying mechanism remains to be elucidated. In this study, we evaluated the fidelity of HPgV-2 and HCV RdRp in an in vitro RNA polymerase reaction system. The results showed higher fidelity of HPgV-2 RdRp than HCV NS5B with respect to the misincorporation rate due to their difference in recognizing nucleoside triphosphate (NTP) substrates. Furthermore, HPgV-2 RdRp showed lower sensitivity than HCV to sofosbuvir, a nucleotide inhibitor against HCV RdRp, which explained the insusceptibility of HPgV-2 to direct-acting antiviral (DAA) therapy against HCV infection. Our results indicate that HPgV-2 could be an excellent model for studying the mechanisms involved in viral polymerase fidelity as well as RNA virus diversity and evolution. IMPORTANCE RNA viruses represent the most important pathogens for humans and animals and exhibit rapid evolution and high adaptive capacity, which is due to the high mutation rates for using the error-prone RNA-dependent RNA polymerase (RdRp) during replication. The fidelity of RdRp is closely associated with viral diversity, fitness, and pathogenesis. Previous studies have shown that the second human pegivirus (HPgV-2) exhibits a highly conserved genome sequence and low intrahost variation, which might be due to the fidelity of HPgV-2 RdRp. In this work, we used a series of in vitro RNA polymerase assays to evaluate the in vitro fidelity of HPgV-2 RdRp and compared it with that of HCV RdRp. The results indicated that HPgV-2 RdRp preserves significantly higher fidelity than HCV RdRp, which might contribute to the conservation of the HPgV-2 genome. The unique feature of HPgV-2 RdRp fidelity provides a new model for investigation of viral RdRp fidelity.

Characterizing viral within-host diversity in fast and non-equilibrium demo-genetic dynamics

High-throughput sequencing has opened the route for a deep assessment of within-host genetic diversity that can be used, e.g., to characterize microbial communities and to infer transmission links in infectious disease outbreaks. The performance of such characterizations and inferences cannot be analytically assessed in general and are often grounded on computer-intensive evaluations. Then, being able to simulate within-host genetic diversity across time under various demo-genetic assumptions is paramount to assess the performance of the approaches of interest. In this context, we built an original model that can be simulated to investigate the temporal evolution of genotypes and their frequencies under various demo-genetic assumptions. The model describes the growth and the mutation of genotypes at the nucleotide resolution conditional on an overall within-host viral kinetics, and can be tuned to generate fast non-equilibrium demo-genetic dynamics. We ran simulations of this model and computed classic diversity indices to characterize the temporal variation of within-host genetic diversity (from high-throughput amplicon sequences) of virus populations under three demographic kinetic models of viral infection. Our results highlight how demographic (viral load) and genetic (mutation, selection, or drift) factors drive variations in within-host diversity during the course of an infection. In particular, we observed a non-monotonic relationship between pathogen population size and genetic diversity, and a reduction of the impact of mutation on diversity when a non-specific host immune response is activated. The large variation in the diversity patterns generated in our simulations suggests that the underlying model provides a flexible basis to produce very diverse demo-genetic scenarios and test, for instance, methods for the inference of transmission links during outbreaks.

The Second Human Pegivirus, a Non-Pathogenic RNA Virus with Low Prevalence and Minimal Genetic Diversity

The second human pegivirus (HPgV-2) is a virus discovered in the plasma of a hepatitis C virus (HCV)-infected patient in 2015 belonging to the pegiviruses of the family Flaviviridae. HPgV-2 has been proved to be epidemiologically associated with and structurally similar to HCV but unrelated to HCV disease and non-pathogenic, but its natural history and tissue tropism remain unclear. HPgV-2 is a unique RNA virus sharing the features of HCV and the first human pegivirus (HPgV-1 or GBV-C). Moreover, distinct from most RNA viruses such as HCV, HPgV-1 and human immunodeficiency virus (HIV), HPgV-2 exhibits much lower genomic diversity, with a high global sequence identity ranging from 93.5 to 97.5% and significantly lower intra-host variation than HCV. The mechanisms underlying the conservation of the HPgV-2 genome are not clear but may include efficient innate immune responses, low immune selection pressure and, possibly, the unique features of the viral RNA-dependent RNA polymerase (RdRP). In this review, we summarize the prevalence, pathogenicity and genetic diversity of HPgV-2 and discuss the possible reasons for the uniformity of its genome sequence, which should elucidate the implications of RNA virus fidelity for attenuated viral vaccines.

Optimized Quantification of Intrahost Viral Diversity in SARS-CoV-2 and Influenza Virus Sequence Data

High error rates of viral RNA-dependent RNA polymerases lead to diverse intra-host viral populations during infection. Errors made during replication that are not strongly deleterious to the virus can lead to the generation of minority variants. However, accurate detection of minority variants in viral sequence data is complicated by errors introduced during sample preparation and data analysis. We used synthetic RNA controls and simulated data to test seven variant calling tools across a range of allele frequencies and simulated coverages. We show that choice of variant caller, and use of replicate sequencing have the most significant impact on single nucleotide variant (SNV) discovery and demonstrate how both allele frequency and coverage thresholds impact both false discovery and false negative rates. We use these parameters to find minority variants in sequencing data from SARS-CoV-2 clinical specimens and provide guidance for studies of intrahost viral diversity using either single replicate data or data from technical replicates. Our study provides a framework for rigorous assessment of technical factors that impact SNV identification in viral samples and establishes heuristics that will inform and improve future studies of intrahost variation, viral diversity, and viral evolution.

IMPORTANCE

When viruses replicate inside a host, the virus replication machinery makes mistakes. Over time, these mistakes create mutations that result in a diverse population of viruses inside the host. Mutations that are neither lethal to the virus, nor strongly beneficial, can lead to minority variants that are minor members of the virus population. However, preparing samples for sequencing can also introduce errors that resemble minority variants, resulting in inclusion of false positive data if not filtered correctly. In this study, we aimed to determine the best methods for identification and quantification of these minority variants by testing the performance of seven commonly used variant calling tools. We used simulated and synthetic data to test their performance against a true set of variants, and then used these studies to inform variant identification in data from clinical SARS-CoV-2 clinical specimens. Together, analyses of our data provide extensive guidance for future studies of viral diversity and evolution.

Detection of Ancient Viruses and Long-Term Viral Evolution

The COVID-19 outbreak has reminded us of the importance of viral evolutionary studies as regards comprehending complex viral evolution and preventing future pandemics. A unique approach to understanding viral evolution is the use of ancient viral genomes. Ancient viruses are detectable in various archaeological remains, including ancient people's skeletons and mummified tissues. Those specimens have preserved ancient viral DNA and RNA, which have been vigorously analyzed in the last few decades thanks to the development of sequencing technologies. Reconstructed ancient pathogenic viral genomes have been utilized to estimate the past pandemics of pathogenic viruses within the ancient human population and long-term evolutionary events. Recent studies revealed the existence of non-pathogenic viral genomes in ancient people's bodies. These ancient non-pathogenic viruses might be informative for inferring their relationships with ancient people's diets and lifestyles. Here, we reviewed the past and ongoing studies on ancient pathogenic and non-pathogenic viruses and the usage of ancient viral genomes to understand their long-term viral evolution.

Low Pathogenicity H7N3 Avian Influenza Viruses Have Higher Within-Host Genetic Diversity Than a Closely Related High Pathogenicity H7N3 Virus in Infected Turkeys and Chickens

Within-host viral diversity offers a view into the early stages of viral evolution occurring after a virus infects a host. In recent years, advances in deep sequencing have allowed for routine identification of low-frequency variants, which are important sources of viral genetic diversity and can potentially emerge as a major virus population under certain conditions. We examined within-host viral diversity in turkeys and chickens experimentally infected with closely related H7N3 avian influenza viruses (AIVs), specifically one high pathogenicity AIV (HPAIV) and two low pathogenicity AIV (LPAIVs) with different neuraminidase protein stalk lengths. Consistent with the high mutation rates of AIVs, an abundance of intra-host single nucleotide variants (iSNVs) at low frequencies of 2–10% was observed in all samples collected. Furthermore, a small number of common iSNVs were observed between turkeys and chickens, and between directly inoculated and contact-exposed birds. Notably, the LPAIVs have significantly higher iSNV diversities and frequencies of nonsynonymous changes than the HPAIV in both turkeys and chickens. These findings highlight the dynamics of AIV populations within hosts and the potential impact of genetic changes, including mutations in the hemagglutinin gene that confers the high pathogenicity pathotype, on AIV virus populations and evolution.

Assessment of Inter-Laboratory Differences in SARS-CoV-2 Consensus Genome Assemblies between Public Health Laboratories in Australia

Whole-genome sequencing of viral isolates is critical for informing transmission patterns and for the ongoing evolution of pathogens, especially during a pandemic. However, when genomes have low variability in the early stages of a pandemic, the impact of technical and/or sequencing errors increases. We quantitatively assessed inter-laboratory differences in consensus genome assemblies of 72 matched SARS-CoV-2-positive specimens sequenced at different laboratories in Sydney, Australia. Raw sequence data were assembled using two different bioinformatics pipelines in parallel, and resulting consensus genomes were compared to detect laboratory-specific differences. Matched genome sequences were predominantly concordant, with a median pairwise identity of 99.997%. Identified differences were predominantly driven by ambiguous site content. Ignoring these produced differences in only 2.3% (5/216) of pairwise comparisons, each differing by a single nucleotide. Matched samples were assigned the same Pango lineage in 98.2% (212/216) of pairwise comparisons, and were mostly assigned to the same phylogenetic clade. However, epidemiological inference based only on single nucleotide variant distances may lead to significant differences in the number of defined clusters if variant allele frequency thresholds for consensus genome generation differ between laboratories. These results underscore the need for a unified, best-practices approach to bioinformatics between laboratories working on a common outbreak problem.

Intra- and inter-host evolution of H9N2 influenza A virus in Japanese quail

Influenza A viruses (IAVs) are constantly evolving. Crucial steps in the infection cycle, such as sialic acid (SA) receptor binding on the host cell surface, can either promote or hamper the emergence of new variants. We previously assessed the relative fitness in Japanese quail of H9N2 variant viruses differing at a single amino acid position, residue 216 in the hemagglutinin (HA) viral surface protein. This site is known to modulate SA recognition. Our prior study generated a valuable set of longitudinal samples from quail transmission groups where the inoculum comprised different mixed populations of HA 216 variant viruses. Here, we leveraged these samples to examine the evolutionary dynamics of viral populations within and between inoculated and naïve contact quails. We found that positive selection dominated HA gene evolution, but fixation of the fittest variant depended on the competition mixture. Analysis of the whole genome revealed further evidence of positive selection acting both within and between hosts. Positive selection drove fixation of variants in non-HA segments within inoculated and contact quails. Importantly, transmission bottlenecks were modulated by the molecular signature at HA 216, revealing viral receptor usage as a determinant of transmitted diversity. Overall, we show that selection strongly shaped the evolutionary dynamics within and between quails. These findings support the notion that selective processes act effectively on IAV populations in poultry hosts, facilitating rapid viral evolution in this ecological niche.

SARS-CoV-2 Infection of Rhesus Macaques Treated Early with Human COVID-19 Convalescent Plasma

Human clinical studies investigating use of convalescent plasma (CP) for treatment of coronavirus disease 2019 (COVID-19) have produced conflicting results. Outcomes in these studies may vary at least partly due to different timing of CP administration relative to symptom onset. The mechanisms of action of CP include neutralizing antibodies but may extend beyond virus neutralization to include normalization of blood clotting and dampening of inflammation. Unresolved questions include the minimum therapeutic titer in the CP units or CP recipient as well as the optimal timing of administration. Here, we show that treatment of macaques with CP within 24 h of infection does not reduce viral shedding in nasal or lung secretions compared to controls and does not detectably improve any clinical endpoint. We also demonstrate that CP administration does not impact viral sequence diversity in vivo, although the selection of a viral sequence variant in both macaques receiving normal human plasma was suggestive of immune pressure. Our results suggest that CP, administered to medium titers, has limited efficacy, even when given very early after infection. Our findings also contribute information important for the continued development of the nonhuman primate model of COVID-19. These results should inform interpretation of clinical studies of CP in addition to providing insights useful for developing other passive immunotherapies and vaccine strategies. IMPORTANCE Antiviral treatment options for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain very limited. One treatment that was explored beginning early in the pandemic (and that is likely to be tested early in future pandemics) is plasma collected from people who have recovered from coronavirus disease 2019 (COVID-19), known as convalescent plasma (CP). We tested if CP reduces viral shedding or disease in a nonhuman primate model. Our results demonstrate that administration of CP 1 day after SARS-CoV-2 infection had no significant impact on viral loads, clinical disease, or sequence diversity, although treatment with normal human plasma resulted in selection of a specific viral variant. Our results demonstrate that passive immunization with CP, even during early infection, provided no significant benefit in a nonhuman primate model of SARS-CoV-2 infection.

A viral ubiquitination switch attenuates innate immunity and triggers nuclear import of virion DNA and infection

Antiviral defense and virus exclusion from the cell nucleus restrict foreign nucleic acid influx and infection. How the genomes of DNA viruses evade cytosolic pattern recognition and cross the nuclear envelope is incompletely understood. Here, we show that the virion protein V of adenovirus functions as a linchpin between the genome and the capsid, thereby securing particle integrity. Absence of protein V destabilizes cytoplasmic particles and promotes premature genome release, raising cytokine levels through the DNA sensor cGAS. Non-ubiquitinable V yields stable virions, genome misdelivery to the cytoplasm, and increased cytokine levels. In contrast, normal protein V is ubiquitinated at the nuclear pore complex, dissociates from the virion depending on the E3 ubiquitin ligase Mib1 and the proteasome, and allows genome delivery into the nucleus for infection. Our data uncover previously unknown cellular and viral mechanisms of viral DNA nuclear import in pathogenesis, vaccination, gene therapy, and synthetic biology.

Long-read sequencing reveals the evolutionary drivers of intra-host diversity across natural RNA mycovirus infections

Intra-host dynamics are a core component of virus evolution but most intra-host data come from a narrow range of hosts or experimental infections. Gaining broader information on the intra-host diversity and dynamics of naturally occurring virus infections is essential to our understanding of evolution across the virosphere. Here we used PacBio long-read HiFi sequencing to characterize the intra-host populations of natural infections of the RNA mycovirus Cryphonectria hypovirus 1 (CHV1). CHV1 is a biocontrol agent for the chestnut blight fungus (Cryphonectria parasitica), which co-invaded Europe alongside the fungus. We characterized the mutational and haplotypic intra-host virus diversity of thirty-eight natural CHV1 infections spread across four locations in Croatia and Switzerland. Intra-host CHV1 diversity values were shaped by purifying selection and accumulation of mutations over time as well as epistatic interactions within the host genome at defense loci. Geographical landscape features impacted CHV1 inter-host relationships through restricting dispersal and causing founder effects. Interestingly, a small number of intra-host viral haplotypes showed high sequence similarity across large geographical distances unlikely to be linked by dispersal.

The evolution of cheating in viruses

The success of many viruses depends upon cooperative interactions between viral genomes. However, whenever cooperation occurs, there is the potential for 'cheats' to exploit that cooperation. We suggest that: (1) the biology of viruses makes viral cooperation particularly susceptible to cheating; (2) cheats are common across a wide range of viruses, including viral entities that are already well studied, such as defective interfering genomes, and satellite viruses. Consequently, the evolutionary theory of cheating could help us understand and manipulate viral dynamics, while viruses also offer new opportunities to study the evolution of cheating.

Use of hemagglutinin and neuraminidase amplicon-based high-throughput sequencing with variant analysis to detect co-infection and resolve identical consensus sequences of seasonal influenza in a university setting

Background

Local transmission of seasonal influenza viruses (IVs) can be difficult to resolve. Here, we study if coupling high-throughput sequencing (HTS) of hemagglutinin (HA) and neuraminidase (NA) genes with variant analysis can resolve strains from local transmission that have identical consensus genome. We analyzed 24 samples collected over four days in January 2020 at a large university in the US. We amplified complete hemagglutinin (HA) and neuraminidase (NA) genomic segments followed by Illumina sequencing. We identified consensus complete HA and NA segments using BLASTn and performed variant analysis on strains whose HA and NA segments were 100% similar.

Results

Twelve of the 24 samples were PCR positive, and we detected complete HA and/or NA segments by de novo assembly in 83.33% (10/12) of them. Similarity and phylogenetic analysis showed that 70% (7/10) of the strains were distinct while the remaining 30% had identical consensus sequences. These three samples also had IAV and IBV co-infection. However, subsequent variant analysis showed that they had distinct variant profiles. While the IAV HA of one sample had no variant, another had a T663C mutation and another had both C1379T and C1589A.

Conclusion

In this study, we showed that HTS coupled with variant analysis of only HA and NA genes can help resolve variants that are closely related. We also provide evidence that during a short time period in the 2019–2020 season, co-infection of IAV and IBV occurred on the university campus and both 2020/2021 and 2021/2022 WHO recommended H1N1 vaccine strains were co-circulating.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06526-5.

Longitudinal linked-read sequencing reveals ecological and evolutionary responses of a human gut microbiome during antibiotic treatment

Gut microbial communities can respond to antibiotic perturbations by rapidly altering their taxonomic and functional composition. However, little is known about the strain-level processes that drive this collective response. Here, we characterize the gut microbiome of a single individual at high temporal and genetic resolution through a period of health, disease, antibiotic treatment, and recovery. We used deep, linked-read metagenomic sequencing to track the longitudinal trajectories of thousands of single nucleotide variants within 36 species, which allowed us to contrast these genetic dynamics with the ecological fluctuations at the species level. We found that antibiotics can drive rapid shifts in the genetic composition of individual species, often involving incomplete genome-wide sweeps of pre-existing variants. These genetic changes were frequently observed in species without obvious changes in species abundance, emphasizing the importance of monitoring diversity below the species level. We also found that many sweeping variants quickly reverted to their baseline levels once antibiotic treatment had concluded, demonstrating that the ecological resilience of the microbiota can sometimes extend all the way down to the genetic level. Our results provide new insights into the population genetic forces that shape individual microbiomes on therapeutically relevant timescales, with potential implications for personalized health and disease.

What we learned in the past year in managing our COVID-19 patients in intensive care units?

Coronavirus disease 2019 is a pandemic, was first recognized at Wuhan province, China in December 2019. The disease spread quickly across the globe, spreading stealthily from human to human through both symptomatic and asymptomatic individuals. A multisystem disease which appears to primarily spread via bio aerosols, it has exhibited a wide clinical spectrum involving multiple organ systems with the respiratory system pathology being the prime cause of morbidity and mortality. Initially unleashing a huge destructive trail at Wuhan China, Lombardy Italy and New York City, it has now spread to all parts of the globe and has actively thrived and mutated into new forms. Health care systems and Governments responded initially with panic, with containment measures giving way to mitigation strategies. The global medical and scientific community has come together and responded to this huge challenge. Professional medical societies quickly laid out "expert" guidelines which were conservative in their approach. Many drugs were re formulated and tested quickly with the help of national and international collaborative groups, helping carve out effective treatment strategies and help build a good scientific foundation for evidence-based medicine. Out of the darkness of chaos, we now have an orderly approach to manage this disease both from a public health preventive and therapeutic standpoint. With preventive measures such as masking and social distancing to the development of highly effective and potent vaccines, the public health success of such measures has been tempered by behavioral responses and resource mobilization. From a therapy standpoint, we now have drugs that were promising but now proven ineffective, and those that are effective when given early during viral pathogenesis or later when immune dysregulation has established, and the goal is to help reign in the destructive cascade. It has been a fascinating journey for mankind and our work here recapitulates the evolution of various aspects of critical care and other inpatient practices which continue to evolve.

Quantitative measures of within-host viral genetic diversity

The genetic diversity of virus populations within their hosts is known to influence disease progression, treatment outcome, drug resistance, cell tropism, and transmission risk, and the study of dynamic changes of genetic heterogeneity can provide insights into the evolution of viruses. Several measures to quantify within-host genetic diversity capturing different aspects of diversity patterns in a sample or population are used, based on incidence, relative frequencies, pairwise distances, or phylogenetic trees. Here, we review and compare several of these measures.

Virus Prevalence and Genetic Diversity Across a Wild Bumblebee Community

Viruses are key population regulators, but we have limited knowledge of the diversity and ecology of viruses. This is even the case in wild host populations that provide ecosystem services, where small fitness effects may have major ecological impacts in aggregate. One such group of hosts are the bumblebees, which have a major role in the pollination of food crops and have suffered population declines and range contractions in recent decades. In this study, we investigate the diversity of four recently discovered bumblebee viruses (Mayfield virus 1, Mayfield virus 2, River Liunaeg virus, and Loch Morlich virus), and two previously known viruses that infect both wild bumblebees and managed honeybees (Acute bee paralysis virus and Slow bee paralysis virus) from isolates in Scotland. We investigate the ecological and environmental factors that determine viral presence and absence. We show that the recently discovered bumblebee viruses were more genetically diverse than the viruses shared with honeybees. Coinfection is potentially important in shaping prevalence: we found a strong positive association between River Liunaeg virus and Loch Morlich virus presence after controlling for host species, location and other relevant ecological variables. We tested for a relationship between environmental variables (temperature, UV radiation, wind speed, and prevalence), but as we had few sampling sites, and thus low power for site-level analyses, we could not conclude anything regarding these variables. We also describe the relationship between the bumblebee communities at our sampling sites. This study represents a first step in the description of predictors of bumblebee infection in the wild.

Alternation between taxonomically divergent hosts is not the major determinant of flavivirus evolution

Flaviviruses display diverse epidemiological and ecological features. Tick-borne and mosquito-borne flaviviruses (TBFV and MBFV, respectively) are important human pathogens that alternate replication in invertebrate vectors and vertebrate hosts. The Flavivirus genus also includes insect-specific viruses (ISFVs) and viruses with unknown invertebrate hosts. It is generally accepted that viruses that alternate between taxonomically different hosts evolve slowly and that the evolution of MBFVs and TBFVs is dominated by strong constraints, with limited episodes of positive selection. We exploited the availability of flavivirus genomes to test these hypotheses and to compare their rates and patterns of evolution. We estimated the substitution rates of CFAV and CxFV (two ISFVs) and, by taking into account the time-frame of measurement, compared them with those of other flaviviruses. Results indicated that CFAV and CxFV display relatively different substitution rates. However, these data, together with estimates for single-host members of the Flaviviridae family, indicated that MBFVs do not display relatively slower evolution. Conversely, TBFVs displayed some of lowest substitution rates among flaviviruses. Analysis of selective patterns over longer evolutionary time-frames confirmed that MBFVs evolve under strong purifying selection. Interestingly, TBFVs and ISFVs did not show extremely different levels of constraint, although TBFVs alternate among hosts, whereas ISFVs do not. Additional results showed that episodic positive selection drove the evolution of MBFVs, despite their high constraint. Positive selection was also detected on two branches of the TBFVs phylogeny that define the seabird clade. Thus, positive selection was much more common during the evolution of arthropod-borne flaviviruses than previously thought. Overall, our data indicate that flavivirus evolutionary patterns are complex and most likely determined by multiple factors, not limited to the alternation between taxonomically divergent hosts. The frequency of both positive and purifying selection, especially in MBFVs, suggests that a minority of sites in the viral polyprotein experience weak constraint and can evolve to generate new viral phenotypes and possibly promote adaptation to new hosts.