Understanding the complex evolution of rapidly mutating viruses with deep sequencing: Beyond the analysis of viral diversity

Comparative analysis between genotypes of adenovirus isolates from hospitalized children with acute respiratory tract infections and clinical manifestations in Wuhan, China, from June 2022 to September 2023

Acute respiratory tract infections (ARTIs) are among the leading causes of morbidity and mortality in children worldwide. Human adenovirus (HAdV) infections are estimated to account for at least 5% of pediatric ARTIs. The circulated genotypes of HAdV and the correlation between genotype and clinical manifestations in Wuhan, China, before and after the complete relaxation of nonpharmaceutical interventions against severe acute respiratory syndrome coronavirus 2, remain unknown. Here, 101 HAdV strains were isolated from throat swab samples collected from hospitalized children with ARTIs who tested positive for HAdV nucleic acid. Of these, sixty-six strains from 2022 and 23 strains from 2023 were successfully genotyped and subjected to phylogenetic analysis based on the hexon, penton base, and fiber genes. Six genotypes, B3, C1, C2, C5, C104, and C108 were identified. HAdV-B3 (84.85%) was the most prevalent type in 2022, while HAdV-C (86.96%), including C1, C2, C108, and C104, was the most prevalent in 2023. These strains were phylogenetically related to strains from Japan, China, and the United States in recent years. When comparing clinical characteristics, pediatric patients infected with B3, C1, C2, C5, C104, or C108 exhibited similar clinical manifestations, primarily fever and cough, but varying interleukin (IL)-10 levels. In conclusion, from June 2022 to September 2023, the circulated genotypes of HAdV in Wuhan included B3, C1, C2, C108, C5, and C104. The endemic pattern of HAdV in Wuhan, China, shifted from species B as the dominant type in 2022 to species C in 2023.

Complementary insights into gut viral genomes: a comparative benchmark of short- and long-read metagenomes using diverse assemblers and binners

BACKGROUND

Metagenome-assembled viral genomes have significantly advanced the discovery and characterization of the human gut virome. However, we lack a comparative assessment of assembly tools on the efficacy of viral genome identification, particularly across next-generation sequencing (NGS) and third-generation sequencing (TGS) data.

RESULTS

We evaluated the efficiency of NGS, TGS, and hybrid assemblers for viral genome discovery using 95 viral-like particle (VLP)-enriched fecal samples sequenced on both Illumina and PacBio platforms. MEGAHIT, metaFlye, and hybridSPAdes emerged as the optimal choices for NGS, TGS, and hybrid datasets, respectively. Notably, these assemblers recovered distinct viral genomes, demonstrating a remarkable degree of complementarity. By combining individual assembler results, we expanded the total number of nonredundant high-quality viral genomes by 4.83 ~ 21.7-fold compared to individual assemblers. Among them, viral genomes from NGS and TGS data have the least overlap, indicating the impact of data type on viral genome recovery. We also evaluated four binning methods, finding that CONCOCT incorporated more unrelated contigs into the same bins, while MetaBAT2, AVAMB, and vRhyme balanced inclusiveness and taxonomic consistency within bins.

CONCLUSIONS

Our findings highlight the challenges in metagenome-driven viral discovery, underscoring tool limitations. We advocate for combined use of multiple assemblers and sequencing technologies when feasible and highlight the urgent need for specialized tools tailored to gut virome assembly. This study contributes essential insights for advancing viral genome research in the context of gut metagenomics. Video Abstract.

Haplotype assignment of longitudinal viral deep sequencing data using covariation of variant frequencies

Longitudinal deep sequencing of viruses can provide detailed information about intra-host evolutionary dynamics including how viruses interact with and transmit between hosts. Many analyses require haplotype reconstruction, identifying which variants are co-located on the same genomic element. Most current methods to perform this reconstruction are based on a high density of variants and cannot perform this reconstruction for slowly evolving viruses. We present a new approach, HaROLD (HAplotype Reconstruction Of Longitudinal Deep sequencing data), which performs this reconstruction based on identifying co-varying variant frequencies using a probabilistic framework. We illustrate HaROLD on both RNA and DNA viruses with synthetic Illumina paired read data created from mixed human cytomegalovirus (HCMV) and norovirus genomes, and clinical datasets of HCMV and norovirus samples, demonstrating high accuracy, especially when longitudinal samples are available.

From Clinical Specimen to Whole Genome Sequencing of A(H3N2) Influenza Viruses: A Fast and Reliable High-Throughput Protocol

(1) Background: Over the last few years, there has been growing interest in the whole genome sequencing (WGS) of rapidly mutating pathogens, such as influenza viruses (IVs), which has led us to carry out in-depth studies on viral evolution in both research and diagnostic settings. We aimed at describing and determining the validity of a WGS protocol that can obtain the complete genome sequence of A(H3N2) IVs directly from clinical specimens. (2) Methods: RNA was extracted from 80 A(H3N2)-positive respiratory specimens. A one-step RT-PCR assay, based on the use of a single set of specific primers, was used to retro-transcribe and amplify the entire IV type A genome in a single reaction, thus avoiding additional enrichment approaches and host genome removal treatments. Purified DNA was quantified; genomic libraries were prepared and sequenced by using Illumina MiSeq platform. The obtained reads were evaluated for sequence quality and read-pair length. (3) Results: All of the study specimens were successfully amplified, and the purified DNA concentration proved to be suitable for NGS (at least 0.2 ng/µL). An acceptable coverage depth for all eight genes of influenza A(H3N2) virus was obtained for 90% (72/80) of the clinical samples with viral loads >105 genome copies/mL. The mean depth of sequencing ranged from 105 to 200 reads per position, with the majority of the mean depth values being above 103 reads per position. The total turnaround time per set of 20 samples was four working days, including sequence analysis. (4) Conclusions: This fast and reliable high-throughput sequencing protocol should be used for influenza surveillance and outbreak investigation.

Towards a Systems Immunology Approach to Understanding Correlates of Protective Immunity against HCV

Over the past decade, tremendous progress has been made in systems biology-based approaches to studying immunity to viral infections and responses to vaccines. These approaches that integrate multiple facets of the immune response, including transcriptomics, serology and immune functions, are now being applied to understand correlates of protective immunity against hepatitis C virus (HCV) infection and to inform vaccine development. This review focuses on recent progress in understanding immunity to HCV using systems biology, specifically transcriptomic and epigenetic studies. It also examines proposed strategies moving forward towards an integrated systems immunology approach for predicting and evaluating the efficacy of the next generation of HCV vaccines.

The effect of variant interference on de novo assembly for viral deep sequencing

BACKGROUND

Viruses have high mutation rates and generally exist as a mixture of variants in biological samples. Next-generation sequencing (NGS) approaches have surpassed Sanger for generating long viral sequences, yet how variants affect NGS de novo assembly remains largely unexplored.

RESULTS

Our results from > 15,000 simulated experiments showed that presence of variants can turn an assembly of one genome into tens to thousands of contigs. This "variant interference" (VI) is highly consistent and reproducible by ten commonly-used de novo assemblers, and occurs over a range of genome length, read length, and GC content. The main driver of VI is pairwise identities between viral variants. These findings were further supported by in silico simulations, where selective removal of minor variant reads from clinical datasets allow the "rescue" of full viral genomes from fragmented contigs.

CONCLUSIONS

These results call for careful interpretation of contigs and contig numbers from de novo assembly in viral deep sequencing.

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.

High levels of unreported intraspecific diversity among RNA viruses in faeces of neonatal piglets with diarrhoea

BACKGROUND

Diarrhoea is a major cause of death in neonate pigs and most of the viruses that cause it are RNA viruses. Next Generation Sequencing (NGS) deeply characterize the genetic diversity among rapidly mutating virus populations at the interspecific as well as the intraspecific level. The diversity of RNA viruses present in faeces of neonatal piglets suffering from diarrhoea in 47 farms, plus 4 samples from non-diarrhoeic piglets has been evaluated by NGS. Samples were selected among the cases submitted to the Veterinary Diagnostic Laboratories of Infectious Diseases of the Universitat Autònoma de Barcelona (Barcelona, Spain) and Universidad de León (León, Spain).

RESULTS

The analyses identified the presence of 12 virus species corresponding to 8 genera of RNA viruses. Most samples were co-infected by several viruses. Kobuvirus and Rotavirus were more commonly reported, with Sapovirus, Astrovirus 3, 4 and 5, Enterovirus G, Porcine epidemic diarrhoea virus, Pasivirus and Posavirus being less frequently detected. Most sequences showed a low identity with the sequences deposited in GenBank, allowing us to propose several new VP4 and VP7 genotypes for Rotavirus B and Rotavirus C.

CONCLUSIONS

Among the cases analysed, Rotaviruses were the main aetiological agents of diarrhoea in neonate pigs. Besides, in a small number of cases Kobuvirus and Sapovirus may also have an aetiological role. Even most animals were co-infected in early life, the association with enteric disease among the other examined viruses was unclear. The NGS method applied successfully characterized the RNA virome present in faeces and detected a high level of unreported intraspecific diversity.

Clearance of hepatitis C virus is associated with early and potent but narrowly-directed, Envelope-specific antibodies

Hepatitis C virus (HCV) is one of very few viruses that are either naturally cleared, or alternatively persist to cause chronic disease. Viral diversity and escape, as well as host adaptive immune factors, are believed to control the outcome. To date, there is limited understanding of the critical, early host-pathogen interactions. The asymptomatic nature of early HCV infection generally prevents identification of the transmitted/founder (T/F) virus, and thus the study of host responses directed against the autologous T/F strain. In this study, 14 rare subjects identified from very early in infection (4–45 days) with varied disease outcomes (n = 7 clearers) were examined in regard to the timing, breadth, and magnitude of the neutralizing antibody (nAb) response, as well as evolution of the T/F strain. Clearance was associated with earlier onset and more potent nAb responses appearing at a mean of 71 days post-infection (DPI), but these responses were narrowly directed against the autologous T/F virus or closely related variants. In contrast, a delayed onset of nAbs (mean 425 DPI) was observed in chronic progressors that appear to have targeted longitudinal variants rather than the T/F strain. The nAb responses in the chronic progressors mapped to known CD81 binding epitopes, and were associated with rapid emergence of new viral variants with reduced CD81 binding. We propose that the prolonged period of viremia in the absence of nAbs in these subjects was associated with an increase in viral diversity, affording the virus greater options to escape nAb pressure once it emerged. These findings indicate that timing of the nAb response is essential for clearance. Further investigation of the specificities of the early nAbs and the factors regulating early induction of protective nAbs is needed.

Dengue drug discovery: Progress, challenges and outlook

In the context of the only available vaccine (DENGVAXIA) that was marketed in several countries, but poses higher risks to unexposed individuals, the development of antivirals for dengue virus (DENV), whilst challenging, would bring significant benefits to public health. Here recent progress in the field of DENV drug discovery made in academic laboratories and industry is reviewed. Characteristics of an ideal DENV antiviral molecule, given the specific immunopathology provoked by this acute viral infection, are described. New chemical classes identified from biochemical, biophysical and phenotypic screens that target viral (especially NS4B) and host proteins, offer promising opportunities for further development. In particular, new methodologies ("omics") can accelerate the discovery of much awaited flavivirus specific inhibitors. Challenges and opportunities in lead identification activities as well as the path to clinical development of dengue drugs are discussed. To galvanize DENV drug discovery, collaborative public-public partnerships and open-access resources will greatly benefit both the DENV research community and DENV patients.

Full-Length Envelope Analyzer (FLEA): A tool for longitudinal analysis of viral amplicons

Next generation sequencing of viral populations has advanced our understanding of viral population dynamics, the development of drug resistance, and escape from host immune responses. Many applications require complete gene sequences, which can be impossible to reconstruct from short reads. HIV env, the protein of interest for HIV vaccine studies, is exceptionally challenging for long-read sequencing and analysis due to its length, high substitution rate, and extensive indel variation. While long-read sequencing is attractive in this setting, the analysis of such data is not well handled by existing methods. To address this, we introduce FLEA (Full-Length Envelope Analyzer), which performs end-to-end analysis and visualization of long-read sequencing data. FLEA consists of both a pipeline (optionally run on a high-performance cluster), and a client-side web application that provides interactive results. The pipeline transforms FASTQ reads into high-quality consensus sequences (HQCSs) and uses them to build a codon-aware multiple sequence alignment. The resulting alignment is then used to infer phylogenies, selection pressure, and evolutionary dynamics. The web application provides publication-quality plots and interactive visualizations, including an annotated viral alignment browser, time series plots of evolutionary dynamics, visualizations of gene-wide selective pressures (such as dN/dS) across time and across protein structure, and a phylogenetic tree browser. We demonstrate how FLEA may be used to process Pacific Biosciences HIV env data and describe recent examples of its use. Simulations show how FLEA dramatically reduces the error rate of this sequencing platform, providing an accurate portrait of complex and variable HIV env populations. A public instance of FLEA is hosted at http://flea.datamonkey.org. The Python source code for the FLEA pipeline can be found at https://github.com/veg/flea-pipeline. The client-side application is available at https://github.com/veg/flea-web-app. A live demo of the P018 results can be found at http://flea.murrell.group/view/P018.

Viral populations constantly evolve and diversify. In this article we introduce a method, FLEA, for reconstructing and visualizing the details of evolutionary changes. FLEA specifically processes data from sequencing platforms that generate reads that are long, but error-prone. To study the evolutionary dynamics of entire genes during viral infection, data is collected via long-read sequencing at discrete time points, allowing us to understand how the virus changes over time. However, the experimental and sequencing process is imperfect, so the resulting data contain not only real evolutionary changes, but also mutations and other genetic artifacts caused by sequencing errors. Our method corrects most of these errors by combining thousands of erroneous sequences into a much smaller number of unique consensus sequences that represent biologically meaningful variation. The resulting high-quality sequences are used for further analysis, such as building an evolutionary tree that tracks and interprets the genetic changes in the viral population over time. FLEA is open source, and is freely available online.

Risk Assessment of Fifth-Wave H7N9 Influenza A Viruses in Mammalian Models

The fifth wave of the H7N9 influenza epidemic in China was distinguished by a sudden increase in human infections, an extended geographic distribution, and the emergence of highly pathogenic avian influenza (HPAI) viruses. Genetically, some H7N9 viruses from the fifth wave have acquired novel amino acid changes at positions involved in mammalian adaptation, antigenicity, and hemagglutinin cleavability. Here, several human low-pathogenic avian influenza (LPAI) and HPAI H7N9 virus isolates from the fifth epidemic wave were assessed for their pathogenicity and transmissibility in mammalian models, as well as their ability to replicate in human airway epithelial cells. We found that an LPAI virus exhibited a similar capacity to replicate and cause disease in two animal species as viruses from previous waves. In contrast, HPAI H7N9 viruses possessed enhanced virulence, causing greater lethargy and mortality, with an extended tropism for brain tissues in both ferret and mouse models. These HPAI viruses also showed signs of adaptation to mammalian hosts by acquiring the ability to fuse at a lower pH threshold than other H7N9 viruses. All of the fifth-wave H7N9 viruses were able to transmit among cohoused ferrets but exhibited a limited capacity to transmit by respiratory droplets, and deep sequencing analysis revealed that the H7N9 viruses sampled after transmission showed a reduced amount of minor variants. Taken together, we conclude that the fifth-wave HPAI H7N9 viruses have gained the ability to cause enhanced disease in mammalian models and with further adaptation may acquire the ability to cause an H7N9 pandemic.IMPORTANCE The potential pandemic risk posed by avian influenza H7N9 viruses was heightened during the fifth epidemic wave in China due to the sudden increase in the number of human infections and the emergence of antigenically distinct LPAI and HPAI H7N9 viruses. In this study, a group of fifth-wave HPAI and LPAI viruses was evaluated for its ability to infect, cause disease, and transmit in small-animal models. The ability of HPAI H7N9 viruses to cause more severe disease and to replicate in brain tissues in animal models as well as their ability to fuse at a lower pH threshold than LPAI H7N9 viruses suggests that the fifth-wave H7N9 viruses have evolved to acquire novel traits with the potential to pose a higher risk to humans. Although the fifth-wave H7N9 viruses have not yet gained the ability to transmit efficiently by air, continuous surveillance and risk assessment remain essential parts of our pandemic preparedness efforts.

Dynamic interactions between RNA viruses and human hosts unravelled by a decade of next generation sequencing

BACKGROUND

Next generation sequencing (NGS) methods have significantly contributed to a paradigm shift in genomic research for nearly a decade now. These methods have been useful in studying the dynamic interactions between RNA viruses and human hosts.

SCOPE OF THE REVIEW

In this review, we summarise and discuss key applications of NGS in studying the host - pathogen interactions in RNA viral infections of humans with examples.

MAJOR CONCLUSIONS

Use of NGS to study globally relevant RNA viral infections have revolutionized our understanding of the within host and between host evolution of these viruses. These methods have also been useful in clinical decision-making and in guiding biomedical research on vaccine design.

GENERAL SIGNIFICANCE

NGS has been instrumental in viral genomic studies in resolving within-host viral genomic variants and the distribution of nucleotide polymorphisms along the full-length of viral genomes in a high throughput, cost effective manner. In the future, novel advances such as long read, single molecule sequencing of viral genomes and simultaneous sequencing of host and pathogens may become the standard of practice in research and clinical settings. This will also bring on new challenges in big data analysis.

Viral communities associated with porcine respiratory disease complex in intensive commercial farms in Sichuan province, China

Porcine respiratory disease complex (PRDC), a common piglet disease, causes substantive economic losses in pig farming. To investigate the viral diversity associated with PRDC, the viral communities in serum and nasal swabs from 26 PRDC-affected piglets were investigated using metagenomics. By deep sequencing and de novo assembly, 17 viruses were identified in two pooled libraries (16 viruses from serum, nine from nasal swabs). Porcine circovirus (PCV)-2, porcine reproductive and respiratory syndrome virus (PRRSV) and pseudorabies virus, all commonly associated with PRDC, were identified in the two pooled samples by metagenomics, but most viruses comprised small linear and circular DNAs (e.g. parvoviruses, bocaviruses and circoviruses). PCR was used to compare the detection rates of each virus in the serum samples from 36 PRDC-affected piglets versus 38 location-matched clinically healthy controls. The average virus category per sample was 6.81 for the PRDC-affected piglets and 4.09 for the controls. Single or co-infections with PCV-2 or PRRSV had very high detection rates in the PRDC-affected piglets. Interestingly, porcine parvovirus (PPV)-2, PPV-3, PPV-6 and torque teno sus virus 1a were significantly associated with PRDC. These results illustrate the complexity of viral communities in the PRDC-affected piglets and highlight the candidate viruses associated with it.