Whole genome sequencing identifies influenza A H3N2 transmission and offers superior resolution to classical typing methods

A Cold Case of Equine Influenza Disentangled with Nanopore Sequencing

Massive sequencing techniques have allowed us to develop straightforward approaches for the whole genome sequencing of viruses, including influenza viruses, generating information that is useful for improving the levels and dimensions of data analysis, even for archival samples. Using the Nanopore platform, we determined the whole genome sequence of an H3N8 equine influenza virus, identified from a 2005 outbreak in Apulia, Italy, whose origin had remained epidemiologically unexplained. The virus was tightly related (>99% at the nucleotide level) in all the genome segments to viruses identified in Poland in 2005–2008 and it was seemingly introduced locally with horse trading for the meat industry. In the phylogenetic analysis based on the eight genome segments, strain ITA/2005/horse/Bari was found to cluster with sub-lineage Florida 2 in the HA and M genes, whilst in the other genes it clustered with strains of the Eurasian lineage, revealing a multi-reassortant nature.

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.

Genome characterization and mutation analysis of human influenza A virus in Thailand

The influenza A viruses have high mutation rates and cause a serious health problem worldwide. Therefore, this study focused on genome characterization of the viruses isolated from Thai patients based on the next-generation sequencing technology. The nasal swabs were collected from patients with influenza-like illness in Thailand during 2017-2018. Then, the influenza A viruses were detected by reverse transcription-quantitative polymerase chain reaction and isolated by MDCK cells. The viral genomes were amplified and sequenced by Illumina MiSeq platform. Whole genome sequences were used for characterization, phylogenetic construction, mutation analysis and nucleotide diversity of the viruses. The result revealed that 90 samples were positive for the viruses including 44 of A/H1N1 and 46 of A/H3N2. Among these, 43 samples were successfully isolated and then the viral genomes of 25 samples were completely amplified. Finally, 17 whole genomes of the viruses (A/H1N1, n=12 and A/H3N2, n=5) were successfully sequenced with an average of 232,578 mapped reads and 1,720 genome coverage per sample. Phylogenetic analysis demonstrated that the A/H1N1 viruses were distinguishable from the recommended vaccine strains. However, the A/H3N2 viruses from this study were closely related to the recommended vaccine strains. The nonsynonymous mutations were found in all genes of both viruses, especially in HA and NA genes. The nucleotide diversity analysis revealed negative selection in the PB1, PA, hemagglutinin (HA) and neuraminidase (NA) genes of the A/H1N1 viruses. High-throughput data in this study allow for genetic characterization of circulating influenza viruses which would be crucial for preparation against pandemic and epidemic outbreaks in the future.

Extensive Hospital In-Ward Clustering Revealed By Molecular Characterization of Influenza A Virus Infection

BACKGROUND

Nosocomial transmission of influenza A virus (InfA) infection is not fully recognized. The aim of this study was to describe the characteristics of hospitalized patients with InfA infections during an entire season and to investigate in-ward transmission at a large, acute-care hospital.

METHODS

During the 2016-17 season, all hospitalized patients ≥18 years old with laboratory-verified (real-time polymerase chain reaction) InfA were identified. Cases were characterized according to age; sex; comorbidity; antiviral therapy; viral load, expressed as cycle threshold values; length of hospital stay; 30-day mortality; and whether the InfA infection met criteria for a health care-associated influenza A infection (HCAI). Respiratory samples positive for InfA that were collected at the same wards within 7 days were chosen for whole-genome sequencing (WGS) and a phylogenetic analysis was performed to detect clustering. For reference, concurrent InfA strains from patients with community-acquired infection were included.

RESULTS

We identified a total of 435 InfA cases, of which 114 (26%) met the HCAI criteria. The overall 30-day mortality rate was higher among patients with HCAI (9.6% vs 4.6% among non-HCAI patients), although the difference was not statistically significant in a multivariable analysis, where age was the only independent risk factor for death (P < .05). We identified 8 closely related clusters (involving ≥3 cases) and another 10 pairs of strains, supporting in-ward transmission.

CONCLUSIONS

We found that the in-ward transmission of InfA occurs frequently and that HCAI may have severe outcomes. WGS may be used for outbreak investigations, as well as for evaluations of the effects of preventive measures.

Influenza classification from short reads with VAPOR facilitates robust mapping pipelines and zoonotic strain detection for routine surveillance applications

Motivation

Influenza viruses represent a global public health burden due to annual epidemics and pandemic potential. Due to a rapidly evolving RNA genome, inter-species transmission, intra-host variation, and noise in short-read data, reads can be lost during mapping, and de novo assembly can be time consuming and result in misassembly. We assessed read loss during mapping and designed a graph-based classifier, VAPOR, for selecting mapping references, assembly validation and detection of strains of non-human origin.

Results

Standard human reference viruses were insufficient for mapping diverse influenza samples in simulation. VAPOR retrieved references for 257 real whole-genome sequencing samples with a mean of >99.8% identity to assemblies, and increased the proportion of mapped reads by up to 13.3% compared to standard references. VAPOR has the potential to improve the robustness of bioinformatics pipelines for surveillance and could be adapted to other RNA viruses.

Availability and implementation

VAPOR is available at https://github.com/connor-lab/vapor.

Supplementary information

Supplementary data are available at Bioinformatics online.

The use of host factors in microbial forensics

Advances have been made in the forensic analysis of microbes and toxins. An underdeveloped and underutilized area in microbial forensics is how the host interacts with microorganisms in a way that provides unique signatures for forensic use. For forensic purposes, an immediate goal is to distinguish a potential victim and innocent person from a perpetrator, and to distinguish between a naturally acquired or intentional infection. Principal methods that are sufficiently developed are characterization of the humoral immune response to microbial antigens including vaccine-induced immunity and detection of antibiotics that may be present in a possible perpetrator. This chapter presents central elements of the host response in a simplified fashion and describes a representative example, which, in the appropriate context, has a high potential of providing evidence that may aid an investigation to distinguish a perpetrator from a victim. This chapter also presents information about the immune system so that the interested reader can have a fuller understanding of the immune response in general.

Metagenomic Nanopore Sequencing of Influenza Virus Direct from Clinical Respiratory Samples

Influenza is a major global public health threat as a result of its highly pathogenic variants, large zoonotic reservoir, and pandemic potential. Metagenomic viral sequencing offers the potential for a diagnostic test for influenza virus which also provides insights on transmission, evolution, and drug resistance and simultaneously detects other viruses. We therefore set out to apply the Oxford Nanopore Technologies sequencing method to metagenomic sequencing of respiratory samples. We generated influenza virus reads down to a limit of detection of 102 to 103 genome copies/ml in pooled samples, observing a strong relationship between the viral titer and the proportion of influenza virus reads (P = 4.7 × 10-5). Applying our methods to clinical throat swabs, we generated influenza virus reads for 27/27 samples with mid-to-high viral titers (cycle threshold [CT ] values, <30) and 6/13 samples with low viral titers (CT values, 30 to 40). No false-positive reads were generated from 10 influenza virus-negative samples. Thus, Nanopore sequencing operated with 83% sensitivity (95% confidence interval [CI], 67 to 93%) and 100% specificity (95% CI, 69 to 100%) compared to the current diagnostic standard. Coverage of full-length virus was dependent on sample composition, being negatively influenced by increased host and bacterial reads. However, at high influenza virus titers, we were able to reconstruct >99% complete sequences for all eight gene segments. We also detected a human coronavirus coinfection in one clinical sample. While further optimization is required to improve sensitivity, this approach shows promise for the Nanopore platform to be used in the diagnosis and genetic analysis of influenza virus and other respiratory viruses.

Nosocomial transmission of influenza: A retrospective cross-sectional study using next generation sequencing at a hospital in England (2012-2014)

BACKGROUND

The extent of transmission of influenza in hospital settings is poorly understood. Next generation sequencing may improve this by providing information on the genetic relatedness of viral strains.

OBJECTIVES

We aimed to apply next generation sequencing to describe transmission in hospital and compare with methods based on routinely-collected data.

METHODS

All influenza samples taken through routine care from patients at University College London Hospitals NHS Foundation Trust (September 2012 to March 2014) were included. We conducted Illumina sequencing and identified genetic clusters. We compared nosocomial transmission estimates defined using classical methods (based on time from admission to sample) and genetic clustering. We identified pairs of cases with space-time links and assessed genetic relatedness.

RESULTS

We sequenced influenza sampled from 214 patients. There were 180 unique genetic strains, 16 (8.8%) of which seeded a new transmission chain. Nosocomial transmission was indicated for 32 (15.0%) cases using the classical definition and 34 (15.8%) based on genetic clustering. Of the 50 patients in a genetic cluster, 11 (22.0%) had known space-time links with other cases in the same cluster. Genetic distances between pairs of cases with space-time links were lower than for pairs without spatial links (P < .001).

CONCLUSIONS

Genetic data confirmed that nosocomial transmission contributes significantly to the hospital burden of influenza and elucidated transmission chains. Prospective next generation sequencing could support outbreak investigations and monitor the impact of infection and control measures.

Genomic analysis of respiratory syncytial virus infections in households and utility in inferring who infects the infant

Infants (under 1-year-old) are at most risk of life threatening respiratory syncytial virus (RSV) disease. RSV epidemiological data alone has been insufficient in defining who acquires infection from whom (WAIFW) within households. We investigated RSV genomic variation within and between infected individuals and assessed its potential utility in tracking transmission in households. Over an entire single RSV season in coastal Kenya, nasal swabs were collected from members of 20 households every 3-4 days regardless of symptom status and screened for RSV nucleic acid. Next generation sequencing was used to generate >90% RSV full-length genomes for 51.1% of positive samples (191/374). Single nucleotide polymorphisms (SNPs) observed during household infection outbreaks ranged from 0-21 (median: 3) while SNPs observed during single-host infection episodes ranged from 0-17 (median: 1). Using the viral genomic data alone there was insufficient resolution to fully reconstruct within-household transmission chains. For households with clear index cases, the most likely source of infant infection was via a toddler (aged 1 to <3 years-old) or school-aged (aged 6 to <12 years-old) co-occupant. However, for best resolution of WAIFW within households, we suggest an integrated analysis of RSV genomic and epidemiological data.

Improved detection of influenza A virus from blue-winged teals by sequencing directly from swab material

Abstract

The greatest diversity of influenza A virus (IAV) is found in wild aquatic birds of the orders Anseriformes and Charadriiformes. In these birds, IAV replication occurs mostly in the intestinal tract. Fecal, cloacal, and/or tracheal swabs are typically collected and tested by real-time RT-PCR (rRT-PCR) and/or by virus isolation in embryonated chicken eggs in order to determine the presence of IAV. Virus isolation may impose bottlenecks that select variant populations that are different from those circulating in nature, and such bottlenecks may result in artifactual representation of subtype diversity and/or underrepresented mixed infections. The advent of next-generation sequencing (NGS) technologies provides an opportunity to explore to what extent IAV subtype diversity is affected by virus isolation in eggs. In the present work, we evaluated the advantage of sequencing by NGS directly from swab material of IAV rRT-PCR-positive swabs collected during the 2013-14 surveillance season in Guatemala and compared to results from NGS after virus isolation. The results highlight the benefit of sequencing IAV genomes directly from swabs to better understand subtype diversity and detection of alternative amino acid motifs that could otherwise escape detection using traditional methods of virus isolation. In addition, NGS sequencing data from swabs revealed reduced presence of defective interfering particles compared to virus isolates. We propose an alternative workflow in which original swab samples positive for IAV by rRT-PCR are first subjected to NGS before attempting viral isolation. This approach should speed the processing of samples and better capture natural IAV diversity.

OPEN RESEARCH BADGES

This article has earned an Open Data Badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. The data is available at https://doi.org/10.5061/dryad.3h2n106.

Evaluation of two workflows for whole genome sequencing-based typing of influenza A viruses

We compared two sample preparation protocols for whole genome sequencing of influenza A viruses. Each protocol was assessed using cDNA quantity and quality and the resulting mean genome coverage after sequencing. Both protocols produced acceptable result for samples with high viral load, whereas one protocol performed slightly better with limited virus count.

Seasonal Genetic Drift of Human Influenza A Virus Quasispecies Revealed by Deep Sequencing

After a pandemic wave in 2009 following their introduction in the human population, the H1N1pdm09 viruses replaced the previously circulating, pre-pandemic H1N1 virus and, along with H3N2 viruses, are now responsible for the seasonal influenza type A epidemics. So far, the evolutionary potential of influenza viruses has been mainly documented by consensus sequencing data. However, like other RNA viruses, influenza A viruses exist as a population of diverse, albeit related, viruses, or quasispecies. Interest in this quasispecies nature has increased with the development of next generation sequencing (NGS) technologies that allow a more in-depth study of the genetic variability. NGS deep sequencing methodologies were applied to determine the whole genome genetic heterogeneity of the three categories of influenza A viruses that circulated in humans between 2007 and 2012 in France, directly from clinical respiratory specimens. Mutation frequencies and single nucleotide polymorphisms were used for comparisons to address the level of natural intrinsic heterogeneity of influenza A viruses. Clear differences in single nucleotide polymorphism profiles between seasons for a given subtype also revealed the constant genetic drift that human influenza A virus quasispecies undergo.

Use of Whole-Genome Sequencing in the Investigation of a Nosocomial Influenza Virus Outbreak

Traditional epidemiological investigation of nosocomial transmission of influenza involves the identification of patients who have the same influenza virus type and who have overlapped in time and place. This method may misidentify transmission where it has not occurred or miss transmission when it has. We used influenza virus whole-genome sequencing (WGS) to investigate an outbreak of influenza A virus infection in a hematology/oncology ward and identified 2 separate introductions, one of which resulted in 5 additional infections and 79 bed-days lost. Results from WGS are becoming rapidly available and may supplement traditional infection control procedures in the investigation and management of nosocomial outbreaks.

Molecular characterization of a nosocomial outbreak of influenza B virus in an acute care hospital setting

Aim

To describe a hospital outbreak of influenza B virus (InfB) infection during season 2015/2016 by combining clinical and epidemiological data with molecular methods.

Methods

Twenty patients diagnosed with InfB from a hospital outbreak over a four-week-period were included. Nasopharyngeal samples (NPS) positive for InfB by multiplex real-time polymerase chain reaction were sent for lineage typing and whole genome sequencing (WGS). Medical records were reviewed retrospectively for data regarding patient characteristics, localization, exposure and outcome, and assembled into a timeline. In order to find possible connections to the hospital outbreak, all patients with a positive NPS for influenza from the region over an extended time period were also reviewed.

Findings

All 20 cases of InfB were of subtype B/Yamagata, and 17 of 20 patients could be linked to each other by either shared room or shared ward. WGS was successful or partially successful for 15 of the 17 viral isolates, and corroborated the epidemiological link supporting a close relationship. In the main affected ward, 19 of 75 inpatients were infected with InfB during the outbreak period, resulting in an attack rate of 25%. One probable case of influenza-related death was identified.

Conclusion

InfB may spread within an acute care hospital, and advanced molecular methods may facilitate assessment of the source and extent of the outbreak. A multi-faceted approach, including rapid diagnosis, early recognition of outbreak situations, simple rules for patient management and the use of regular infection control measures, may prevent nosocomial transmission of influenza virus.

INSaFLU: an automated open web-based bioinformatics suite "from-reads" for influenza whole-genome-sequencing-based surveillance

BACKGROUND

A new era of flu surveillance has already started based on the genetic characterization and exploration of influenza virus evolution at whole-genome scale. Although this has been prioritized by national and international health authorities, the demanded technological transition to whole-genome sequencing (WGS)-based flu surveillance has been particularly delayed by the lack of bioinformatics infrastructures and/or expertise to deal with primary next-generation sequencing (NGS) data.

RESULTS

We developed and implemented INSaFLU ("INSide the FLU"), which is the first influenza-oriented bioinformatics free web-based suite that deals with primary NGS data (reads) towards the automatic generation of the output data that are actually the core first-line "genetic requests" for effective and timely influenza laboratory surveillance (e.g., type and sub-type, gene and whole-genome consensus sequences, variants' annotation, alignments and phylogenetic trees). By handling NGS data collected from any amplicon-based schema, the implemented pipeline enables any laboratory to perform multi-step software intensive analyses in a user-friendly manner without previous advanced training in bioinformatics. INSaFLU gives access to user-restricted sample databases and projects management, being a transparent and flexible tool specifically designed to automatically update project outputs as more samples are uploaded. Data integration is thus cumulative and scalable, fitting the need for a continuous epidemiological surveillance during the flu epidemics. Multiple outputs are provided in nomenclature-stable and standardized formats that can be explored in situ or through multiple compatible downstream applications for fine-tuned data analysis. This platform additionally flags samples as "putative mixed infections" if the population admixture enrolls influenza viruses with clearly distinct genetic backgrounds, and enriches the traditional "consensus-based" influenza genetic characterization with relevant data on influenza sub-population diversification through a depth analysis of intra-patient minor variants. This dual approach is expected to strengthen our ability not only to detect the emergence of antigenic and drug resistance variants but also to decode alternative pathways of influenza evolution and to unveil intricate routes of transmission.

CONCLUSIONS

In summary, INSaFLU supplies public health laboratories and influenza researchers with an open "one size fits all" framework, potentiating the operationalization of a harmonized multi-country WGS-based surveillance for influenza virus. INSaFLU can be accessed through https://insaflu.insa.pt .