High Throughput Sequencing for the Detection and Characterization of RNA Viruses

Wastewater surveillance together with metaviromic data revealed the unusual resurgence of infectious diseases after the first wave of the COVID-19 outbreak

How to address public health priorities after COVID-19 is becoming a critical task. To this end, we conducted wastewater surveillance for six leading pathogens, namely, SARS-CoV-2, norovirus, rotavirus, influenza A virus (IAV), enteroviruses and respiratory syncytial virus (RSV), in Nanchang city from January to April 2023. Metaviromic sequencing was conducted at the 1st, 4th, 7th, 9th, 12th and 14th weeks to reveal the dynamics of viral pathogens that were not covered by qPCR. Amplicon sequencing of the conserved region of norovirus GI and GII and the rotavirus and region encoding nonstructural protein of RSV was also conducted weekly. The results showed that after a rapid decrease in SARS-CoV-2 sewage concentrations occurred in January 2023, surges of norovirus, rotavirus, IAV and RSV started at the 6th, 7th, 8th and 11th weeks, respectively. The dynamics of the sewage concentrations of norovirus, rotavirus, IAV and RSV were consistent with the off-season resurgence of the above infectious diseases. Notably, peak sewage concentrations of norovirus GI, GII, rotavirus, IAV and RSV were found at the 6th, 3rd, 7th, 7th and 8th weeks, respectively. Astroviruses also resurge after the 7th week, as revealed by metaviromic data, suggesting that wastewater surveillance together with metaviromic data provides an essential early warning tool for revealing patterns of infectious disease resurgence.

Refining detection methods for emerging SARS-CoV-2 mutants in wastewater: A case study on the Omicron variants

COVID-19 is an ongoing public health threat worldwide driven by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Wastewater surveillance has emerged as a complementary tool to clinical surveillance to control the COVID-19 pandemic. With the emergence of new variants of SARS-CoV-2, accumulated mutations that occurred in the SARS-CoV-2 genome raise new challenges for RT-qPCR diagnosis used in wastewater surveillance. There is a pressing need to develop refined methods for modifying primer/probes to better detect these emerging variants in wastewater. Here, we exemplified this process by focusing on the Omicron variants, for which we have developed and validated a modified detection method. We first modified the primers/probe mismatches of three assays commonly used in wastewater surveillance according to in silico analysis results for the mutations of 882 sequences collected during the fifth-wave outbreak in Hong Kong, and then evaluated them alongside the seven original assays. The results showed that five of seven original assays had better sensitivity for detecting Omicron variants, with the limits of detection (LoDs) ranging from 1.53 to 2.76 copies/μL. UCDC-N1 and Charité-E sets had poor performances, having LoDs higher than 10 copies/μL and false-positive/false-negative results in wastewater testing, probably due to the mismatch and demonstrating the need for modification of primer/probe sequences. The modified assays exhibited higher sensitivity and specificity, along with better reproducibility in detecting 81 wastewater samples. In addition, the sequencing results of six wastewater samples by Illumina also validated the presence of mismatches in the primer/probe binding sites of the three assays. This study highlights the importance of re-configuration of the primer-probe sets and refinements for the sequences to ensure the diagnostic effectiveness of RT-qPCR detection.

Metagenomic sequencing detects human respiratory and enteric viruses in air samples collected from congregate settings

Innovative methods for evaluating virus risk and spread, independent of test-seeking behavior, are needed to improve routine public health surveillance, outbreak response, and pandemic preparedness. Throughout the COVID-19 pandemic, environmental surveillance strategies, including wastewater andair sampling, have been used alongside widespread individual-based SARS-CoV-2 testing programs to provide population-level data. These environmental surveillance strategies have predominantly relied on pathogen-specific detection methods to monitor viruses through space and time. However, this provides a limited picture of the virome present in an environmental sample, leaving us blind to most circulating viruses. In this study, we explore whether pathogen-agnostic deep sequencing can expand the utility of air sampling to detect many human viruses. We show that sequence-independent single-primer amplification sequencing of nucleic acids from air samples can detect common and unexpected human respiratory and enteric viruses, including influenza virus type A and C, respiratory syncytial virus, human coronaviruses, rhinovirus, SARS-CoV-2, rotavirus, mamastrovirus, and astrovirus.

Metagenomic sequencing detects human respiratory and enteric viruses in air samples collected from congregate settings

Innovative methods for evaluating virus risk and spread, independent of test-seeking behavior, are needed to improve routine public health surveillance, outbreak response, and pandemic preparedness. Throughout the COVID-19 pandemic, environmental surveillance strategies, including wastewater and air sampling, have been used alongside widespread individual-based SARS-CoV-2 testing programs to provide population-level data. These environmental surveillance strategies have predominantly relied on pathogen-specific detection methods to monitor viruses through space and time. However, this provides a limited picture of the virome present in an environmental sample, leaving us blind to most circulating viruses. In this study, we explore whether pathogen-agnostic deep sequencing can expand the utility of air sampling to detect many human viruses. We show that sequence-independent single-primer amplification sequencing of nucleic acids from air samples can detect common and unexpected human respiratory and enteric viruses, including influenza virus type A and C, respiratory syncytial virus, human coronaviruses, rhinovirus, SARS-CoV-2, rotavirus, mamastrovirus, and astrovirus.

The Underrated Gut Microbiota Helminths, Bacteriophages, Fungi, and Archaea

The microbiota inhabits the gastrointestinal tract, providing essential capacities to the host. The microbiota is a crucial factor in intestinal health and regulates intestinal physiology. However, microbiota disturbances, named dysbiosis, can disrupt intestinal homeostasis, leading to the development of diseases. Classically, the microbiota has been referred to as bacteria, though other organisms form this complex group, including viruses, archaea, and eukaryotes such as fungi and protozoa. This review aims to clarify the role of helminths, bacteriophages, fungi, and archaea in intestinal homeostasis and diseases, their interaction with bacteria, and their use as therapeutic targets in intestinal maladies.

Development of a targeted amplicon sequencing method for genotyping Cyclospora cayetanensis from fresh produce and clinical samples with enhanced genomic resolution and sensitivity

Outbreaks of cyclosporiasis, an enteric illness caused by the parasite Cyclospora cayetanensis, have been associated with consumption of various types of fresh produce. Although a method is in use for genotyping C. cayetanensis from clinical specimens, the very low abundance of C. cayetanensis in food and environmental samples presents a greater challenge. To complement epidemiological investigations, a molecular surveillance tool is needed for use in genetic linkage of food vehicles to cyclosporiasis illnesses, estimation of the scope of outbreaks or clusters of illness, and determination of geographical areas involved. We developed a targeted amplicon sequencing (TAS) assay that incorporates a further enrichment step to gain the requisite sensitivity for genotyping C. cayetanensis contaminating fresh produce samples. The TAS assay targets 52 loci, 49 of which are located in the nuclear genome, and encompasses 396 currently known SNP sites. The performance of the TAS assay was evaluated using lettuce, basil, cilantro, salad mix, and blackberries inoculated with C. cayetanensis oocysts. A minimum of 24 markers were haplotyped even at low contamination levels of 10 oocysts in 25 g leafy greens. The artificially contaminated fresh produce samples were included in a genetic distance analysis based on haplotype presence/absence with publicly available C. cayetanensis whole genome sequence assemblies. Oocysts from two different sources were used for inoculation, and samples receiving the same oocyst preparation clustered together, but separately from the other group, demonstrating the utility of the assay for genetically linking samples. Clinical fecal samples with low parasite loads were also successfully genotyped. This work represents a significant advance in the ability to genotype C. cayetanensis contaminating fresh produce along with greatly expanding the genomic diversity included for genetic clustering of clinical specimens.

Bioinformatic Tools for NGS-Based Metagenomics to Improve the Clinical Diagnosis of Emerging, Re-Emerging and New Viruses

Epidemics and pandemics have occurred since the beginning of time, resulting in millions of deaths. Many such disease outbreaks are caused by viruses. Some viruses, particularly RNA viruses, are characterized by their high genetic variability, and this can affect certain phenotypic features: tropism, antigenicity, and susceptibility to antiviral drugs, vaccines, and the host immune response. The best strategy to face the emergence of new infectious genomes is prompt identification. However, currently available diagnostic tests are often limited for detecting new agents. High-throughput next-generation sequencing technologies based on metagenomics may be the solution to detect new infectious genomes and properly diagnose certain diseases. Metagenomic techniques enable the identification and characterization of disease-causing agents, but they require a large amount of genetic material and involve complex bioinformatic analyses. A wide variety of analytical tools can be used in the quality control and pre-processing of metagenomic data, filtering of untargeted sequences, assembly and quality control of reads, and taxonomic profiling of sequences to identify new viruses and ones that have been sequenced and uploaded to dedicated databases. Although there have been huge advances in the field of metagenomics, there is still a lack of consensus about which of the various approaches should be used for specific data analysis tasks. In this review, we provide some background on the study of viral infections, describe the contribution of metagenomics to this field, and place special emphasis on the bioinformatic tools (with their capabilities and limitations) available for use in metagenomic analyses of viral pathogens.

Investigating the effect of ribavirin treatment on genetic mutations in Crimean-Congo haemorrhagic fever virus (CCHFV) through next-generation sequencing

Crimean-Congo haemorrhagic fever (CCHF) is the most widespread tick-borne viral haemorrhagic fever affecting humans, and yet a licensed drug against the virus (CCHFV) is still not available. While several studies have suggested the efficacy of ribavirin against CCHFV, current literature remains inconclusive. In this study, we have utilised next-generation sequencing to investigate the mutagenic effect of ribavirin on the CCHFV genome during clinical disease. Samples collected from CCHF patients receiving ribavirin treatment or supportive care only at Sivas Cumhuriyet University Hospital, Turkey, were analysed. By comparing the frequency of mutations in each group, we found little evidence of an overall mutagenic effect. This suggests that ribavirin, administered at the acute stages of CCHFV infection (at the World Health Organization-recommended dose) is unable to induce lethal mutagenesis that would cause an extinction event in the CCHFV population and reduce viremia.

NGS method by library enrichment for rapid pestivirus purity testing in biologics

NGS sequencing was evaluated to understand its added value for animal health vaccine candidates. We have previously established the proof of concept for its application in purity testing on several Master Seeds. Here we evaluate the NGS method after enrichment to detect pestiviruses. To achieve this, we conducted a spiking study using 6 viruses, consisting of 3 pestiviruses and 3 other RNA-viruses at different concentrations into cell suspension. A deep Illumina random sequencing of all nucleic acids (DNA and RNA) was performed. The bioinformatics analysis including both assembly into contigs and annotation were processed using viral public databases for the spiked viruses' identification. Here we present the results of spiking experiments for the simultaneous spike of 6 viruses at 100-10 and 1 TCID₅₀/ml. Using Illumina sequencing, the 3 pestiviruses were all detected at the highest concentration, and even at the lowest one such as 1 TCID₅₀/ml for CSFV. Regarding the other viruses, they were not detected at all. Overall, the study showed consistent results for specific detection of pestiviruses with an increase of sensitivity after enrichment. The sensitivity of NGS evaluated by virus spiking experiments of cells demonstrated that NGS method is a valuable and sensitive tool for specific agent detection required in purity testing during vaccine development. This NGS method should be considered as an alternative tool of current purity testing for the prospective testing of biological products.

Next Generation Sequencing Approaches to Characterize the Respiratory Tract Virome

The COVID-19 pandemic and heightened perception of the risk of emerging viral infections have boosted the efforts to better understand the virome or complete repertoire of viruses in health and disease, with a focus on infectious respiratory diseases. Next-generation sequencing (NGS) is widely used to study microorganisms, allowing the elucidation of bacteria and viruses inhabiting different body systems and identifying new pathogens. However, NGS studies suffer from a lack of standardization, in particular, due to various methodological approaches and no single format for processing the results. Here, we review the main methodological approaches and key stages for studies of the human virome, with an emphasis on virome changes during acute respiratory viral infection, with applications for clinical diagnostics and epidemiologic analyses.

Targeted genomic sequencing with probe capture for discovery and surveillance of coronaviruses in bats

Public health emergencies like SARS, MERS, and COVID-19 have prioritized surveillance of zoonotic coronaviruses, resulting in extensive genomic characterization of coronavirus diversity in bats. Sequencing viral genomes directly from animal specimens remains a laboratory challenge, however, and most bat coronaviruses have been characterized solely by PCR amplification of small regions from the best-conserved gene. This has resulted in limited phylogenetic resolution and left viral genetic factors relevant to threat assessment undescribed. In this study, we evaluated whether a technique called hybridization probe capture can achieve more extensive genome recovery from surveillance specimens. Using a custom panel of 20,000 probes, we captured and sequenced coronavirus genomic material in 21 swab specimens collected from bats in the Democratic Republic of the Congo. For 15 of these specimens, probe capture recovered more genome sequence than had been previously generated with standard amplicon sequencing protocols, providing a median 6.1-fold improvement (ranging up to 69.1-fold). Probe capture data also identified five novel alpha- and betacoronaviruses in these specimens, and their full genomes were recovered with additional deep sequencing. Based on these experiences, we discuss how probe capture could be effectively operationalized alongside other sequencing technologies for high-throughput, genomics-based discovery and surveillance of bat coronaviruses.

Mycovirus-encoded suppressors of RNA silencing: Possible allies or enemies in the use of RNAi to control fungal disease in crops

Plants, fungi, and many other eukaryotes have evolved an RNA interference (RNAi) mechanism that is key for regulating gene expression and the control of pathogens. RNAi inhibits gene expression, in a sequence-specific manner, by recognizing and deploying cognate double-stranded RNA (dsRNA) either from endogenous sources (e.g. pre-micro RNAs) or exogenous origin (e.g. viruses, dsRNA, or small interfering RNAs, siRNAs). Recent studies have demonstrated that fungal pathogens can transfer siRNAs into plant cells to suppress host immunity and aid infection, in a mechanism termed cross-kingdom RNAi. New technologies, based on RNAi are being developed for crop protection against insect pests, viruses, and more recently against fungal pathogens. One example, is host-induced gene silencing (HIGS), which is a mechanism whereby transgenic plants are modified to produce siRNAs or dsRNAs targeting key transcripts of plants, or their pathogens or pests. An alternative gene regulation strategy that also co-opts the silencing machinery is spray-induced gene silencing (SIGS), in which dsRNAs or single-stranded RNAs (ssRNAs) are applied to target genes within a pathogen or pest. Fungi also use their RNA silencing machinery against mycoviruses (fungal viruses) and mycoviruses can deploy virus-encoded suppressors of RNAi (myco-VSRs) as a counter-defence. We propose that myco-VSRs may impact new dsRNA-based management methods, resulting in unintended outcomes, including suppression of management by HIGS or SIGS. Despite a large diversity of mycoviruses being discovered using high throughput sequencing, their biology is poorly understood. In particular, the prevalence of mycoviruses and the cellular effect of their encoded VSRs are under-appreciated when considering the deployment of HIGS and SIGS strategies. This review focuses on mycoviruses, their VSR activities in fungi, and the implications for control of pathogenic fungi using RNAi.

Implementing a user-friendly format to analyze PRRSV next-generation sequencing results and associating breeding herd production performance with number of PRRSV strains and recombination events

The open reading frames (ORF)5 represents approximately 4% of the porcine reproductive and respiratory syndrome virus (PRRSV)-2 genome (whole-PRRSV) and is often determined by the Sanger technique, which rarely detects >1 PRRSV strain if present in the sample. Next-generation sequencing (NGS) may provide a more appropriate method of detecting multiple PRRSV strains in one sample. This work assessed the effect of PRRSV genetic variability and recombination events, using NGS, on the time-to-low prevalence (TTLP) and total losses in breeding herds (n 20) that detected a PRRSV outbreak and adopted measures to eliminate PRRSV. Serum, lung or live virus inoculation material collected within 3-weeks of outbreak, and subsequently, processing fluids (PFs) were tested for PRRSV by RT-qPCR and NGS. Recovered whole-PRRSV or partial sequences were used to characterize within and between herd PRRSV genetic variability. Whole-PRRSV was recovered in five out of six (83.3%) lung, 16 out of 22 (72.73%) serum and in five out of 95 (5.26%) PF. Whole-PRRSV recovered from serum or lung were used as farm referent strains in 16 out of 20 (80%) farms. In four farms, only partial genome sequences were recovered and used as farm referent strains. At least two wild-type PRRSV strains (wt-PRRSV) were circulating simultaneously in 18 out of 20 (90%) and at least one vaccine-like strain co-circulating in eight out of 20 (40%) farms. PRRSV recombination events were detected in 12 farms (59%), been 10 out of 12 between wt-PRRSV and two out of 12 between wt-PRRSV and vaccine-like strains. Farms having ≥3 strains had a 12-week increase TTLP versus herds ≤2 strains detected. Farms with ≤2 strains (n 10) had 1837 and farms with no recombination events detected (n 8) had 1827 fewer piglet losses per 1000 sows versus farms with ≥3 PRRSV strains (n 8) or detected recombination (n 10), respectively. NGS outcomes and novel visualization methods provided more thorough insight into PRRSV dynamics, genetic variability, detection of multiple strains co-circulating in breeding herds and helped establish practical guidelines for using PRRSV NGS outputs.

ProbeTools: designing hybridization probes for targeted genomic sequencing of diverse and hypervariable viral taxa

Background

Sequencing viruses in many specimens is hindered by excessive background material from hosts, microbiota, and environmental organisms. Consequently, enrichment of target genomic material is necessary for practical high-throughput viral genome sequencing. Hybridization probes are widely used for enrichment in many fields, but their application to viral sequencing faces a major obstacle: it is difficult to design panels of probe oligo sequences that broadly target many viral taxa due to their rapid evolution, extensive diversity, and genetic hypervariability. To address this challenge, we created ProbeTools, a package of bioinformatic tools for generating effective viral capture panels, and for assessing coverage of target sequences by probe panel designs in silico. In this study, we validated ProbeTools by designing a panel of 3600 probes for subtyping the hypervariable haemagglutinin (HA) and neuraminidase (NA) genome segments of avian-origin influenza A viruses (AIVs). Using in silico assessment of AIV reference sequences and in vitro capture on egg-cultured viral isolates, we demonstrated effective performance by our custom AIV panel and ProbeTools’ suitability for challenging viral probe design applications.

Results

Based on ProbeTool’s in silico analysis, our panel provided broadly inclusive coverage of 14,772 HA and 11,967 NA reference sequences. For each reference sequence, we calculated the percentage of nucleotide positions covered by our panel in silico; 90% of HA and NA references sequences had at least 90.8 and 95.1% of their nucleotide positions covered respectively. We also observed effective in vitro capture on a representative collection of 23 egg-cultured AIVs that included isolates from wild birds, poultry, and humans and representatives from all HA and NA subtypes. Forty-two of forty-six HA and NA segments had over 98.3% of their nucleotide positions significantly enriched by our custom panel. These in vitro results were further used to validate ProbeTools’ in silico coverage assessment algorithm; 89.2% of in silico predictions were concordant with in vitro results.

Conclusions

ProbeTools generated an effective panel for subtyping AIVs that can be deployed for genomic surveillance, outbreak prevention, and pandemic preparedness. Effective probe design against hypervariable AIV targets also validated ProbeTools’ design and coverage assessment algorithms, demonstrating their suitability for other challenging viral capture applications.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08790-4.

HPV Integration Site Mapping: A Rapid Method of Viral Integration Site (VIS) Analysis and Visualization Using Automated Workflows in CLC Microbial Genomics

Human papillomavirus (HPV) integration within the host genome may contribute to carcinogenesis through various disruptive mechanisms. With next-generation sequencing (NGS), identification of viral and host genomic breakpoints and chimeric sequences are now possible. However, a simple, streamlined bioinformatics workflow has been non-existent until recently. Here, we tested two new, automated workflows in CLC Microbial Genomics, i.e., Viral Hybrid Capture (VHC) Data Analysis and Viral Integration Site (VIS) Identification for software performance and efficiency. The workflows embedded with HPV and human reference genomes were used to analyze a publicly available NGS dataset derived from pre- and cancerous HPV+ cervical cytology of 21 Gabonese women. The VHC and VIS workflow median runtimes were 19 and 7 min per sample, respectively. The VIS dynamic graphical outputs included read mappings, virus-host genomic breakpoints, and virus-host integration circular plots. Key findings, including disrupted and nearby genes, were summarized in an auto-generated report. Overall, the VHC and VIS workflows proved to be a rapid and accurate means of localizing viral-host integration site(s) and identifying disrupted and neighboring human genes. Applying HPV VIS-mapping to pre- or invasive tumors will advance our understanding of viral oncogenesis and facilitate the discovery of prognostic biomarkers and therapeutic targets.

Probe Capture Enrichment Methods for HIV and HCV Genome Sequencing and Drug Resistance Genotyping

Human immunodeficiency virus (HIV) infections remain a significant public health concern worldwide. Over the years, sophisticated sequencing technologies such as next-generation sequencing (NGS) have emerged and been utilized to monitor the spread of HIV drug resistance (HIVDR), identify HIV drug resistance mutations, and characterize transmission dynamics. Similar applications also apply to the Hepatitis C virus (HCV), another bloodborne viral pathogen with significant intra-host genetic diversity. Several advantages to using NGS over conventional Sanger sequencing include increased data throughput, scalability, cost-effectiveness when batched sample testing is performed, and sensitivity for quantitative detection of minority resistant variants. However, NGS alone may fail to detect genomes from pathogens present in low copy numbers. As with all sequencing platforms, the primary determinant in achieving quality sequencing data is the quality and quantity of the initial template input. Samples containing degraded RNA/DNA and/or low copy number have been a consistent sequencing challenge. To overcome this limitation probe capture enrichment is a method that has recently been employed to target, enrich, and sequence the genome of a pathogen present in low copies, and for compromised specimens that contain poor quality nucleic acids. It involves the hybridization of sequence-specific DNA or RNA probes to a target sequence, which is followed by an enrichment step via PCR to increase the number of copies of the targeted sequences after which the samples are subjected to NGS procedures. This method has been performed on pathogens such as bacteria, fungus, and viruses and allows for the sequencing of complete genomes, with high coverage. Post NGS, data analysis can be performed through various bioinformatics pipelines which can provide information on genetic diversity, genotype, virulence, and drug resistance. This article reviews how probe capture enrichment helps to increase the likelihood of sequencing HIV and HCV samples that contain low viral loads and/or are compromised.

Diversity and ecological footprint of Global Ocean RNA viruses

DNA viruses are increasingly recognized as influencing marine microbes and microbe-mediated biogeochemical cycling. However, little is known about global marine RNA virus diversity, ecology, and ecosystem roles. In this study, we uncover patterns and predictors of marine RNA virus community- and "species"-level diversity and contextualize their ecological impacts from pole to pole. Our analyses revealed four ecological zones, latitudinal and depth diversity patterns, and environmental correlates for RNA viruses. Our findings only partially parallel those of cosampled plankton and show unexpectedly high polar ecological interactions. The influence of RNA viruses on ecosystems appears to be large, as predicted hosts are ecologically important. Moreover, the occurrence of auxiliary metabolic genes indicates that RNA viruses cause reprogramming of diverse host metabolisms, including photosynthesis and carbon cycling, and that RNA virus abundances predict ocean carbon export.

Epidemiological significance of the occurrence and persistence of rotaviruses in water and sewage: a critical review and proposal for routine microbiological monitoring

Globally, waterborne gastroenteritis attributable to rotaviruses is on the increase due to the rapid increase in population growth, poor socioeconomic conditions, and drastic changes in climatic conditions. The burden of diarrhea is quite alarming in developing nations where the majority of the populations still rely on untreated surface water that is usually polluted for their immediate water needs. Humans and animals of all ages are affected by rotaviruses. In humans, the preponderance of cases occurs in children under 5 years. Global efforts in advancing water/wastewater treatment technologies have not yet realized the objective of complete viral removal from wastewater. Most times, surface waters are impacted heavily by inadequately treated wastewater run-offs thereby exposing people or animals to preventable health risks. The relative stability of rotaviruses in aquatic matrices during wastewater treatment, poor correlation of bacteriological indicators with the presence of rotaviruses, and their infectiousness at a low dose informed the proposal for inclusion in the routine microbiological water screening panel. Environmental monitoring data have been shown to provide early warnings that can complement clinical data used to monitor the impact of current rotavirus vaccination in a community. This review was therefore undertaken to critically appraise rotavirus excretion and emission pathways, and the existence, viability and persistence in the receiving aquatic milieu. The efficiency of the current wastewater treatment modality for rotavirus removal, correlation of the current bacteriological water quality assessment strategy, public health risks and current laboratory methods for an epidemiological study were also discussed.

Review of genome sequencing technologies in molecular characterization of influenza A viruses in swine

The rapidly evolving antigenic diversity of influenza A virus (IAV) genomes in swine makes it imperative to detect emerging novel strains and track their circulation. We analyzed in our review the sequencing technologies used for subtyping and characterizing swine IAV genomes. Google Scholar, PubMed, and International Nucleotide Sequence Database Collaboration (INSDC) database searches identified 216 studies that have utilized Sanger, second-, and third-generation sequencing techniques to subtype and characterize swine IAV genomes up to 31 March 2021. Sanger dideoxy sequencing was by far the most widely used sequencing technique for generating either full-length (43.0%) or partial (31.0%) IAV genomes in swine globally; however, in the last decade, other sequencing platforms such as Illumina have emerged as serious competitors for the generation of whole-genome sequences of swine IAVs. Although partial HA and NA gene sequences were sufficient to determine swine IAV subtypes, whole-genome sequences were critical for determining reassortments and identifying unusual or less frequently occurring IAV subtypes. The combination of Sanger and second-generation sequencing technologies also greatly improved swine IAV characterization. In addition, the rapidly evolving third-generation sequencing platform, MinION, appears promising for on-site, real-time sequencing of complete swine IAV genomes. With a higher raw read accuracy, the use of the MinION could enhance the scalability of swine IAV testing in the field and strengthen the swine IAV disease outbreak response.

Exploring Virome Diversity in Public Data in South America as an Approach for Detecting Viral Sources From Potentially Emerging Viruses

The South American continent presents a great diversity of biomes, whose ecosystems are constantly threatened by the expansion of human activity. The emergence and re-emergence of viral populations with impact on the human population and ecosystem have shown increases in the last decades. In deference to the growing accumulation of genomic data, we explore the potential of South American-related public databases to detect signals that contribute to virosphere research. Therefore, our study aims to investigate public databases with emphasis on the surveillance of viruses with medical and ecological relevance. Herein, we profiled 120 "sequence read archives" metagenomes from 19 independent projects from the last decade. In a coarse view, our analyses identified only 0.38% of the total number of sequences from viruses, showing a higher proportion of RNA viruses. The metagenomes with the most important viral sequences in the analyzed environmental models were 1) aquatic samples from the Amazon River, 2) sewage from Brasilia, and 3) soil from the state of São Paulo, while the models of animal transmission were detected in mosquitoes from Rio Janeiro and Bats from Amazonia. Also, the classification of viral signals into operational taxonomic units (OTUs) (family) allowed us to infer from metadata a probable host range in the virome detected in each sample analyzed. Further, several motifs and viral sequences are related to specific viruses with emergence potential from Togaviridae, Arenaviridae, and Flaviviridae families. In this context, the exploration of public databases allowed us to evaluate the scope and informative capacity of sequences from third-party public databases and to detect signals related to viruses of clinical or environmental importance, which allowed us to infer traits associated with probable transmission routes or signals of ecological disequilibrium. The evaluation of our results showed that in most cases the size and type of the reference database, the percentage of guanine-cytosine (GC), and the length of the query sequences greatly influence the taxonomic classification of the sequences. In sum, our findings describe how the exploration of public genomic data can be exploited as an approach for epidemiological surveillance and the understanding of the virosphere.

OUP accepted manuscript

Chronic enterovirus infections can cause significant morbidity, particularly in immunocompromised patients. This study describes a fatal case associated with a chronic untypeable enterovirus infection in an immunocompromised patient admitted to a Dutch university hospital over nine months. We aimed to identify the enterovirus genotype responsible for the infection and to determine potential evolutionary changes. Long-read sequencing was performed using viral targeted sequence capture on four respiratory and one faecal sample. Phylogenetic analysis was performed using a maximum likelihood method, along with a root-to-tip regression and time-scaled phylogenetic analysis to estimate evolutionary changes between sample dates. Intra-host variant detection, using a Fixed Ploidy algorithm, and selection pressure, using a Fixed Effect Likelihood and a Mixed Effects Model of Evolution, were also used to explore the patient samples. Near-complete genomes of enterovirus C104 (EV-C104) were recovered in all respiratory samples but not in the faecal sample. The recovered genomes clustered with a recently reported EV-C104 from Belgium in August 2018. Phylodynamic analysis including ten available EV-C104 genomes, along with the patient sequences, estimated the most recent common ancestor to occur in the middle of 2005 with an overall estimated evolution rate of 2.97 × 10⁻³ substitutions per year. Although positive selection pressure was identified in the EV-C104 reference sequences, the genomes recovered from the patient samples alone showed an overall negative selection pressure in multiple codon sites along the genome. A chronic infection resulting in respiratory failure from a relatively rare enterovirus was observed in a transplant recipient. We observed an increase in single-nucleotide variations between sample dates from a rapidly declining patient, suggesting mutations are weakly deleterious and have not been purged during selection. This is further supported by the persistence of EV-C104 in the patient, despite the clearance of other viral infections. Next-generation sequencing with viral enrichment could be used to detect and characterise challenging samples when conventional workflows are insufficient.

Predicting the capsid architecture of phages from metagenomic data

Tailed phages are viruses that infect bacteria and are the most abundant biological entities on Earth. Their ecological, evolutionary, and biogeochemical roles in the planet stem from their genomic diversity. Known tailed phage genomes range from 10 to 735 kilobase pairs thanks to the size variability of the protective protein capsids that store them. However, the role of tailed phage capsids’ diversity in ecosystems is unclear. A fundamental gap is the difficulty of associating genomic information with viral capsids in the environment. To address this problem, here, we introduce a computational approach to predict the capsid architecture (T-number) of tailed phages using the sequence of a single gene—the major capsid protein. This approach relies on an allometric model that relates the genome length and capsid architecture of tailed phages. This allometric model was applied to isolated phage genomes to generate a library that associated major capsid proteins and putative capsid architectures. This library was used to train machine learning methods, and the most computationally scalable model investigated (random forest) was applied to human gut metagenomes. Compared to isolated phages, the analysis of gut data reveals a large abundance of mid-sized (T = 7) capsids, as expected, followed by a relatively large frequency of jumbo-like tailed phage capsids (T ≥ 25) and small capsids (T = 4) that have been under-sampled. We discussed how to increase the method’s accuracy and how to extend the approach to other viruses. The computational pipeline introduced here opens the doors to monitor the ongoing evolution and selection of viral capsids across ecosystems.