Proficiency Testing of Virus Diagnostics Based on Bioinformatics Analysis of Simulated In Silico High-Throughput Sequencing Data Sets.

Quality management and independent assessment of high-throughput sequencing-based virus diagnostics have not yet been established as a mandatory approach for ensuring comparable results. The sensitivity and specificity of viral high-throughput sequence data analysis are highly affected by bioinformatics processing using publicly available and custom tools and databases and thus differ widely between individuals and institutions. Here we present the results of the COMPARE [Collaborative Management Platform for Detection and Analyses of (Re-)emerging and Foodborne Outbreaks in Europe] in silico virus proficiency test. An artificial, simulated in silico data set of Illumina HiSeq sequences was provided to 13 different European institutes for bioinformatics analysis to identify viral pathogens in high-throughput sequence data. Comparison of the participants' analyses shows that the use of different tools, programs, and databases for bioinformatics analyses can impact the correct identification of viral sequences from a simple data set. The identification of slightly mutated and highly divergent virus genomes has been shown to be most challenging. Furthermore, the interpretation of the results, together with a fictitious case report, by the participants showed that in addition to the bioinformatics analysis, the virological evaluation of the results can be important in clinical settings. External quality assessment and proficiency testing should become an important part of validating high-throughput sequencing-based virus diagnostics and could improve the harmonization, comparability, and reproducibility of results. There is a need for the establishment of international proficiency testing, like that established for conventional laboratory tests such as PCR, for bioinformatics pipelines and the interpretation of such results.

HEVnet: a One Health, collaborative, interdisciplinary network and sequence data repository for enhanced hepatitis E virus molecular typing, characterisation and epidemiological investigations.

Hepatitis E virus (HEV) is a common cause of acute hepatitis worldwide. In Europe, HEV is a zoonosis transmitted via contaminated pork meat or other pork food products. Genotype 3 is the most prevalent HEV type in the animal reservoir, as well as in humans. Despite an increased incidence of hepatitis E across Europe, much remains unknown about its spread, sources and transmission routes. A One Health approach is crucial to better understand the (molecular) epidemiology of HEV. HEVnet was established in April 2017 as a network and database for sharing sequences and accompanying metadata collected from human, animal, food and environmental sources. HEVnet members working in the public health, veterinary health, food, environmental and blood safety sectors have submitted 1,615 HEV sequences from nine countries as at January 2019. Most are from humans (89%), and sequences of animal (5%), food (6%) or environmental (0.3%) origin are rare. Metadata for human sequences capture mostly sex (93%), year of birth (92%) and sampling (100%); data on region of sampling (37%) and clinical information (hospitalisation 27%, symptoms 20% or mortality 8%) are limited. HEVnet aims to expand into a global network capable of performing cross-sectoral and supranational studies, with a joint repository of molecular and epidemiological data on HEV.

Usability of the international HAVNet hepatitis A virus database for geographical annotation, backtracing and outbreak detection.

BackgroundHAVNet is an international laboratory network sharing sequences and corresponding metadata on hepatitis A virus in an online database. Aim: We give an overview of the epidemiological and genetic data and assess the usability of the present dataset for geographical annotation, backtracing and outbreak detection. Methods: A descriptive analysis was performed on the timeliness, completeness, epidemiological data and geographic coverage of the dataset. Length and genomic region of the sequences were reviewed as well as the numerical and geographical distribution of the genotypes. The geographical signal in the sequences was assessed based on a short common nt stretch using a 100% identity analysis. Results: The 9,211 reports were heterogeneous for completeness and timeliness, and for length and genomic region of the sequences. Some parts of the world were not represented by the sequences. Geographical differences in prevalence of HAV genotypes described previously could be confirmed with this dataset and for a third (1,075/3,124) of the included sequences, 100% identity of the short common sequence coincided with an identical country of origin. Conclusion: Analysis of a subset of short, shared sequences indicates that a geographical annotation on the level of individual countries is possible with the HAVNet data. If the current incompleteness and heterogeneity of the data can be improved on, HAVNet could become very useful as a worldwide reference set for geographical annotation and for backtracing and outbreak detection.

Norovirus genotype profiles associated with foodborne transmission, 1999-2012.

Worldwide, noroviruses are a leading cause of gastroenteritis. They can be transmitted from person to person directly or indirectly through contaminated food, water, or environments. To estimate the proportion of foodborne infections caused by noroviruses on a global scale, we used norovirus transmission and genotyping information from multiple international outbreak surveillance systems (Noronet, CaliciNet, EpiSurv) and from a systematic review of peer-reviewed literature. The proportion of outbreaks caused by food was determined by genotype and/or genogroup. Analysis resulted in the following final global profiles: foodborne transmission is attributed to 10% (range 9%%-11%) of all genotype GII.4 outbreaks, 27% (25%-30%) of outbreaks caused by all other single genotypes, and 37% (24%%-52%) of outbreaks caused by mixtures of GII.4 and other noroviruses. When these profiles are applied to global outbreak surveillance data, results indicate that ≈14% of all norovirus outbreaks are attributed to food.

Proposal for a unified norovirus nomenclature and genotyping.

Noroviruses belong to a genus of genetically diverse viruses within the family Caliciviridae and cause acute gastroenteritis in humans and animals. They are subdivided into genogroups, each of which further segregates into genotypes. Until recently, a new genotype was based on a defined pairwise distance cutoff of complete VP1 sequences, but with the increasing number of available norovirus sequences, this cutoff is no longer accurate, and sequences in the public database have been misclassified. In this paper, we demonstrate that the pairwise distance cutoff method can no longer be used and outline a phylogenetic approach to classify noroviruses. Furthermore, we propose a dual nomenclature using both ORF1 and VP1 sequences, as recombination is common and recognizing recombinant viruses may be relevant. With the continuing emergence of new norovirus lineages, we propose to coordinate nomenclature of new norovirus genotypes through an international norovirus working group.

Metagenomic Surveillance of Viral Gastroenteritis in a Public Health Setting.

Norovirus is the primary cause of viral gastroenteritis (GE). To investigate norovirus epidemiology, there is a need for whole-genome sequencing and reference sets consisting of complete genomes. To investigate the potential of shotgun metagenomic sequencing on the Illumina platform for whole-genome sequencing, 71 reverse transcriptase quantitative PCR (RT-qPCR) norovirus positive-feces (threshold cycle [CT], <30) samples from norovirus surveillance within The Netherlands were subjected to metagenomic sequencing. Data were analyzed through an in-house next-generation sequencing (NGS) analysis workflow. Additionally, we assessed the potential of metagenomic sequencing for the surveillance of off-target viruses that are of importance for public health, e.g., sapovirus, rotavirus A, enterovirus, parechovirus, aichivirus, adenovirus, and bocaparvovirus. A total of 60 complete and 10 partial norovirus genomes were generated, representing 7 genogroup I capsid genotypes and 12 genogroup II capsid genotypes. In addition to the norovirus genomes, the metagenomic approach yielded partial or complete genomes of other viruses for 39% of samples from children and 6.7% of samples from adults, including adenovirus 41 (N = 1); aichivirus 1 (N = 1); coxsackievirus A2 (N = 2), A4 (N = 2), A5 (N = 1), and A16 (N = 1); bocaparvovirus 1 (N = 1) and 3 (N = 1); human parechovirus 1 (N = 2) and 3 (N = 1); Rotavirus A (N = 1); and a sapovirus GI.7 (N = 1). The sapovirus GI.7 was initially not detected through RT-qPCR and warranted an update of the primer and probe set. Metagenomic sequencing on the Illumina platform robustly determines complete norovirus genomes and may be used to broaden gastroenteritis surveillance by capturing off-target enteric viruses. IMPORTANCE Viral gastroenteritis results in significant morbidity and mortality in vulnerable individuals and is primarily caused by norovirus. To investigate norovirus epidemiology, there is a need for whole-genome sequencing and reference sets consisting of full genomes. Using surveillance samples sent to the Dutch National Institute for Public Health and the Environment (RIVM), we compared metagenomics against conventional techniques, such as RT-qPCR and Sanger-sequencing, with norovirus as the target pathogen. We determined that metagenomics is a robust method to generate complete norovirus genomes, in parallel to many off-target pathogenic enteric virus genomes, thereby broadening our surveillance efforts. Moreover, we detected a sapovirus that was not detected by our validated gastroenteritis RT-qPCR panel, which exemplifies the strength of metagenomics. Our study shows that metagenomics can be used for public health gastroenteritis surveillance, the generation of reference-sets for molecular epidemiology, and how it compares to current surveillance strategies.

Integrating genome-based informatics to modernize global disease monitoring, information sharing, and response.

The rapid advancement of genome technologies holds great promise for improving the quality and speed of clinical and public health laboratory investigations and for decreasing their cost. The latest generation of genome DNA sequencers can provide highly detailed and robust information on disease-causing microbes, and in the near future these technologies will be suitable for routine use in national, regional, and global public health laboratories. With additional improvements in instrumentation, these next- or third-generation sequencers are likely to replace conventional culture-based and molecular typing methods to provide point-of-care clinical diagnosis and other essential information for quicker and better treatment of patients. Provided there is free-sharing of information by all clinical and public health laboratories, these genomic tools could spawn a global system of linked databases of pathogen genomes that would ensure more efficient detection, prevention, and control of endemic, emerging, and other infectious disease outbreaks worldwide.

Selection of a phylogenetically informative region of the norovirus genome for outbreak linkage.

The recognition of a common source norovirus outbreak is supported by finding identical norovirus sequences in patients. Norovirus sequencing has been established in many (national) public health laboratories and academic centers, but often partial and different genome sequences are used. Therefore, agreement on a target sequence of sufficient diversity to resolve links between outbreaks is crucial. Although harmonization of laboratory methods is one of the keystone activities of networks that have the aim to identify common source norovirus outbreaks, this has proven difficult to accomplish, particularly in the international context. Here, we aimed at providing a method enabling identification of the genomic region informative of a common source norovirus outbreak by bio-informatic tools. The data set of 502 unique full length capsid gene sequences available from the public domain, combined with epidemiological data including linkage information was used to build over 3,000 maximum likelihood (ML) trees for different sequence lengths and regions. All ML trees were evaluated for robustness and specificity of clustering of known linked norovirus outbreaks against the background diversity of strains. Great differences were seen in the robustness of commonly used PCR targets for cluster detection. The capsid gene region spanning nucleotides 900-1,400 was identified as the region optimally substituting for the full length capsid region. Reliability of this approach depends on the quality of the background data set, and we recommend periodic reassessment of this growing data set. The approach may be applicable to multiple sequence-based data sets of other pathogens.

Regional importation and asymmetric within-country spread of SARS-CoV-2 variants of concern in the Netherlands.

Variants of concern (VOCs) of SARS-CoV-2 have caused resurging waves of infections worldwide. In the Netherlands, Alpha, Beta, Gamma and Delta variants circulated widely between September 2020 and August 2021. To understand how various control measures had impacted the spread of these VOCs, we analyzed 39,844 SARS-CoV-2 genomes collected under the Dutch national surveillance program. We found that all four VOCs were introduced before targeted flight restrictions were imposed on countries where the VOCs first emerged. Importantly, foreign introductions, predominantly from other European countries, continued during these restrictions. Our findings show that flight restrictions had limited effectiveness in deterring VOC introductions due to the strength of regional land travel importation risks. We also found that the Alpha and Delta variants largely circulated more populous regions with international connections after their respective introduction before asymmetric bidirectional transmissions occurred with the rest of the country and the variant dominated infections in the Netherlands. As countries consider scaling down SARS-CoV-2 surveillance efforts in the post-crisis phase of the pandemic, our results highlight that robust surveillance in regions of early spread is important for providing timely information for variant detection and outbreak control.

Regional importation and asymmetric within-country spread of SARS-CoV-2 variants of concern in the Netherlands.

Background: Variants of concern (VOCs) of SARS-CoV-2 have caused resurging waves of infections worldwide. In the Netherlands, the Alpha, Beta, Gamma, and Delta VOCs circulated widely between September 2020 and August 2021. We sought to elucidate how various control measures, including targeted flight restrictions, had impacted the introduction and spread of these VOCs in the Netherlands. Methods: We performed phylogenetic analyses on 39,844 SARS-CoV-2 genomes collected under the Dutch national surveillance program. Results: We found that all four VOCs were introduced before targeted flight restrictions were imposed on countries where the VOCs first emerged. Importantly, foreign introductions, predominantly from other European countries, continued during these restrictions. After their respective introductions into the Netherlands, the Alpha and Delta VOCs largely circulated within more populous regions of the country with international connections before asymmetric bidirectional transmissions occurred with the rest of the country and the VOC became the dominant circulating lineage. Conclusions: Our findings show that flight restrictions had limited effectiveness in deterring VOC introductions due to the strength of regional land travel importation risks. As countries consider scaling down SARS-CoV-2 surveillance efforts in the post-crisis phase of the pandemic, our results highlight that robust surveillance in regions of early spread is important for providing timely information for variant detection and outbreak control. Funding: None.

An integrated approach to identifying international foodborne norovirus outbreaks.

International foodborne norovirus outbreaks can be difficult to recognize when using standard outbreak investigation methods. In a novel approach, we provide step-wise selection criteria to identify clusters of outbreaks that may involve an internationally distributed common foodborne source. After computerized linking of epidemiologic data to aligned sequences, we retrospectively identified 100 individually reported outbreaks that potentially represented 14 international common source events in Europe during 1999-2008. Analysis of capsid sequences of outbreak strains (n = 1,456), showed that ≈7% of outbreaks reported to the Foodborne Viruses in Europe database were part of an international event (range 2%-9%), compared with 0.4% identified through standard epidemiologic investigations. Our findings point to a critical gap in surveillance and suggest that international collaboration could have increased the number of recognized international foodborne outbreaks. Real-time exchange of combined epidemiologic and molecular data is needed to validate our findings through timely trace-backs of clustered outbreaks.

Novel opportunities for NGS-based one health surveillance of foodborne viruses.

Foodborne viral infections rank among the top 5 causes of disease, with noroviruses and hepatitis A causing the greatest burden globally. Contamination of foods by infected food handlers or through environmental pollution are the main sources of foodborne illness, with a lesser role for consumption of products from infected animals. Viral partial genomic sequencing has been used for more than two decades to track foodborne outbreaks and whole genome or metagenomics next-generation-sequencing (NGS) are new additions to the toolbox of food microbiology laboratories. We discuss developments in the field of targeted and metagenomic NGS, with an emphasis on application in food virology, the challenges and possible solutions towards future routine application.

Selection tool for foodborne norovirus outbreaks.

Detection of pathogens in the food chain is limited mainly to bacteria, and the globalization of the food industry enables international viral foodborne outbreaks to occur. Outbreaks from 2002 through 2006 recorded in a European norovirus surveillance database were investigated for virologic and epidemiologic indicators of food relatedness. The resulting validated multivariate logistic regression model comparing foodborne (n = 224) and person-to-person (n = 654) outbreaks was used to create a practical web-based tool that can be limited to epidemiologic parameters for nongenotyping countries. Non-genogroup-II.4 outbreaks, higher numbers of cases, and outbreaks in restaurants or households characterized (sensitivity = 0.80, specificity = 0.86) foodborne outbreaks and reduced the percentage of outbreaks requiring source-tracing to 31%. The selection tool enabled prospectively focused follow-up. Use of this tool is likely to improve data quality and strain typing in current surveillance systems, which is necessary for identification of potential international foodborne outbreaks.

The COMPARE Data Hubs.

Data sharing enables research communities to exchange findings and build upon the knowledge that arises from their discoveries. Areas of public and animal health as well as food safety would benefit from rapid data sharing when it comes to emergencies. However, ethical, regulatory and institutional challenges, as well as lack of suitable platforms which provide an infrastructure for data sharing in structured formats, often lead to data not being shared or at most shared in form of supplementary materials in journal publications. Here, we describe an informatics platform that includes workflows for structured data storage, managing and pre-publication sharing of pathogen sequencing data and its analysis interpretations with relevant stakeholders.

Overview of Virus Metagenomic Classification Methods and Their Biological Applications.

Metagenomics poses opportunities for clinical and public health virology applications by offering a way to assess complete taxonomic composition of a clinical sample in an unbiased way. However, the techniques required are complicated and analysis standards have yet to develop. This, together with the wealth of different tools and workflows that have been proposed, poses a barrier for new users. We evaluated 49 published computational classification workflows for virus metagenomics in a literature review. To this end, we described the methods of existing workflows by breaking them up into five general steps and assessed their ease-of-use and validation experiments. Performance scores of previous benchmarks were summarized and correlations between methods and performance were investigated. We indicate the potential suitability of the different workflows for (1) time-constrained diagnostics, (2) surveillance and outbreak source tracing, (3) detection of remote homologies (discovery), and (4) biodiversity studies. We provide two decision trees for virologists to help select a workflow for medical or biodiversity studies, as well as directions for future developments in clinical viral metagenomics.

Molecular surveillance of norovirus, 2005-16: an epidemiological analysis of data collected from the NoroNet network.

BACKGROUND: The development of a vaccine for norovirus requires a detailed understanding of global genetic diversity of noroviruses. We analysed their epidemiology and diversity using surveillance data from the NoroNet network. METHODS: We included genetic sequences of norovirus specimens obtained from outbreak investigations and sporadic gastroenteritis cases between 2005 and 2016 in Europe, Asia, Oceania, and Africa. We genotyped norovirus sequences and analysed sequences that overlapped at open reading frame (ORF) 1 and ORF2. Additionally, we assessed the sampling date and country of origin of the first reported sequence to assess when and where novel drift variants originated. FINDINGS: We analysed 16 635 norovirus sequences submitted between Jan 1, 2005, to Nov 17, 2016, of which 1372 (8·2%) sequences belonged to genotype GI, 15 256 (91·7%) to GII, and seven (<0·1%) to GIV.1. During this period, 26 different norovirus capsid genotypes circulated and 22 different recombinant genomes were found. GII.4 drift variants emerged with 2-3-year periodicity up to 2012, but not afterwards. Instead, the GII.4 Sydney capsid seems to persist through recombination, with a novel recombinant of GII.P16-GII.4 Sydney 2012 variant detected in 2014 in Germany (n=1) and the Netherlands (n=1), and again in 2016 in Japan (n=2), China (n=8), and the Netherlands (n=3). The novel GII.P17-GII.17, first reported in Asia in 2014, has circulated widely in Europe in 2015-16 (GII.P17 made up a highly variable proportion of all sequences in each country [median 11·3%, range 4·2-53·9], as did GII.17 [median 6·3%, range 0-44·5]). GII.4 viruses were more common in outbreaks in health-care settings (2239 [37·2%] of 6022 entries) compared with other genotypes (101 [12·5%] of 809 entries for GI and 263 [13·5%] of 1941 entries for GII non-GII.Pe-GII.4 or GII.P4-GII.4). INTERPRETATION: Continuous changes in the global norovirus genetic diversity highlight the need for sustained global norovirus surveillance, including assessment of possible immune escape and evolution by recombination, to provide a full overview of norovirus epidemiology for future vaccine policy decisions. FUNDING: European Union's Horizon 2020 grant COMPARE, ZonMw TOP grant, the Virgo Consortium funded by the Dutch Government, and the Hungarian Scientific Research Fund.

Probabilities in norovirus outbreak diagnosis.

BACKGROUND: Noroviruses are recognized as the most common cause of outbreaks of acute gastroenteritis. Yet, diagnostic testing for norovirus is based mostly on RNA detection by RT-PCR, which is not widely available. While antigen detection tests (ELISAs) are easier to perform, they are in general less sensitive. OBJECTIVES: Our aim was to provide a scientific basis for declaring norovirus as the causative agent of an outbreak of acute gastroenteritis. STUDY DESIGN: Statistical analysis used binomial distribution to determine the minimal number of positive samples, and the probability of detecting the required number of positive samples, for different tests, required to assign norovirus as the causative agent of an outbreak of acute gastroenteritis. RESULTS: For either a standard RT-PCR or a commercially available ELISA, finding only 1 sample positive out of 2, 3 or 4 samples is sufficient to assign norovirus as the causative agent of an outbreak of acute gastroenteritis. However, when ELISA is used, the probability of detecting this required minimum number of positive samples is low when small numbers of samples are tested (57% when 2 samples are tested; 72% when 3 samples are tested). In order to reach a 90% probability of detecting a norovirus outbreak (false negativity at outbreak level <10%), at least 3 samples should be tested using RT-PCR, and 6 samples when using an ELISA. CONCLUSIONS: The sensitivity for NoV outbreak diagnosis will increase from 57% to 92%, or from 84% to 96%, for ELISA or RT-PCR respectively, when sample size increases from 2 to 6. Thus, using ELISA instead of RT-PCR for the detection of norovirus in stool samples will result in considerable numbers of false negative outbreaks unless a minimum of 6 samples are tested per outbreak.