Metagenomic approaches to identifying infectious agents

Characterisation of the Upper Respiratory Tract Virome of Feedlot Cattle and Its Association with Bovine Respiratory Disease

Bovine respiratory disease (BRD) is a major health problem within the global cattle industry. This disease has a complex aetiology, with viruses playing an integral role. In this study, metagenomics was used to sequence viral nucleic acids in the nasal swabs of BRD-affected cattle. The viruses detected included those that are well known for their association with BRD in Australia (bovine viral diarrhoea virus 1), as well as viruses known to be present but not fully characterised (bovine coronavirus) and viruses that have not been reported in BRD-affected cattle in Australia (bovine rhinitis, bovine influenza D, and bovine nidovirus). The nasal swabs from a case-control study were subsequently tested for 10 viruses, and the presence of at least one virus was found to be significantly associated with BRD. Some of the more recently detected viruses had inconsistent associations with BRD. Full genome sequences for bovine coronavirus, a virus increasingly associated with BRD, and bovine nidovirus were completed. Both viruses belong to the Coronaviridae family, which are frequently associated with disease in mammals. This study has provided greater insights into the viral pathogens associated with BRD and highlighted the need for further studies to more precisely elucidate the roles viruses play in BRD.

Side-by-Side Comparison of Post-Entry Quarantine and High Throughput Sequencing Methods for Virus and Viroid Diagnosis

Rapid and safe access to new plant genetic stocks is crucial for primary plant industries to remain profitable, sustainable, and internationally competitive. Imported plant species may spend several years in Post Entry Quarantine (PEQ) facilities, undergoing pathogen testing which can impact the ability of plant industries to quickly adapt to new global market opportunities by accessing new varieties. Advances in high throughput sequencing (HTS) technologies provide new opportunities for a broad range of fields, including phytosanitary diagnostics. In this study, we compare the performance of two HTS methods (RNA-Seq and sRNA-Seq) with that of existing PEQ molecular assays in detecting and identifying viruses and viroids from various plant commodities. To analyze the data, we tested several bioinformatics tools which rely on different approaches, including direct-read, de novo, and reference-guided assembly. We implemented VirusReport, a new portable, scalable, and reproducible nextflow pipeline that analyses sRNA datasets to detect and identify viruses and viroids. We raise awareness of the need to evaluate cross-sample contamination when analyzing HTS data routinely and of using methods to mitigate index cross-talk. Overall, our results suggest that sRNA analyzed using VirReport provides opportunities to improve quarantine testing at PEQ by detecting all regulated exotic viruses from imported plants in a single assay.

Application of a strain-level shotgun metagenomics approach on food samples: resolution of the source of a Salmonella food-borne outbreak

Food-borne outbreak investigation currently relies on the time-consuming and challenging bacterial isolation from food, to be able to link food-derived strains to more easily obtained isolates from infected people. When no food isolate can be obtained, the source of the outbreak cannot be unambiguously determined. Shotgun metagenomics approaches applied to the food samples could circumvent this need for isolation from the suspected source, but require downstream strain-level data analysis to be able to accurately link to the human isolate. Until now, this approach has not yet been applied outside research settings to analyse real food-borne outbreak samples. In September 2019, a Salmonella outbreak occurred in a hotel school in Bruges, Belgium, affecting over 200 students and teachers. Following standard procedures, the Belgian National Reference Center for human salmonellosis and the National Reference Laboratory for Salmonella in food and feed used conventional analysis based on isolation, serotyping and MLVA (multilocus variable number tandem repeat analysis) comparison, followed by whole-genome sequencing, to confirm the source of the contamination over 2 weeks after receipt of the sample, which was freshly prepared tartar sauce in a meal cooked at the school. Our team used this outbreak as a case study to deliver a proof of concept for a short-read strain-level shotgun metagenomics approach for source tracking. We received two suspect food samples: the full meal and some freshly made tartar sauce served with this meal, requiring the use of raw eggs. After analysis, we could prove, without isolation, that Salmonella was present in both samples, and we obtained an inferred genome of a Salmonella enterica subsp. enterica serovar Enteritidis that could be linked back to the human isolates of the outbreak in a phylogenetic tree. These metagenomics-derived outbreak strains were separated from sporadic cases as well as from another outbreak circulating in Europe at the same time period. This is, to our knowledge, the first Salmonella food-borne outbreak investigation uniquely linking the food source using a metagenomics approach and this in a fast time frame.

Next-generation diagnostics: virus capture facilitates a sensitive viral diagnosis for epizootic and zoonotic pathogens including SARS-CoV-2

BACKGROUND

The detection of pathogens in clinical and environmental samples using high-throughput sequencing (HTS) is often hampered by large amounts of background information, which is especially true for viruses with small genomes. Enormous sequencing depth can be necessary to compile sufficient information for identification of a certain pathogen. Generic HTS combining with in-solution capture enrichment can markedly increase the sensitivity for virus detection in complex diagnostic samples.

METHODS

A virus panel based on the principle of biotinylated RNA baits was developed for specific capture enrichment of epizootic and zoonotic viruses (VirBaits). The VirBaits set was supplemented by a SARS-CoV-2 predesigned bait set for testing recent SARS-CoV-2-positive samples. Libraries generated from complex samples were sequenced via generic HTS (without enrichment) and afterwards enriched with the VirBaits set. For validation, an internal proficiency test for emerging epizootic and zoonotic viruses (African swine fever virus, Ebolavirus, Marburgvirus, Nipah henipavirus, Rift Valley fever virus) was conducted.

RESULTS

The VirBaits set consists of 177,471 RNA baits (80-mer) based on about 18,800 complete viral genomes targeting 35 epizootic and zoonotic viruses. In all tested samples, viruses with both DNA and RNA genomes were clearly enriched ranging from about 10-fold to 10,000-fold for viruses including distantly related viruses with at least 72% overall identity to viruses represented in the bait set. Viruses showing a lower overall identity (38% and 46%) to them were not enriched but could nonetheless be detected based on capturing conserved genome regions. The internal proficiency test supports the improved virus detection using the combination of HTS plus targeted enrichment but also points to the risk of cross-contamination between samples.

CONCLUSIONS

The VirBaits approach showed a high diagnostic performance, also for distantly related viruses. The bait set is modular and expandable according to the favored diagnostics, health sector, or research question. The risk of cross-contamination needs to be taken into consideration. The application of the RNA-baits principle turned out to be user friendly, and even non-experts can easily use the VirBaits workflow. The rapid extension of the established VirBaits set adapted to actual outbreak events is possible as shown for SARS-CoV-2. Video abstract.

Next-generation diagnostics: virus capture facilitates a sensitive viral diagnosis for epizootic and zoonotic pathogens including SARS-CoV-2

BACKGROUND

The detection of pathogens in clinical and environmental samples using high-throughput sequencing (HTS) is often hampered by large amounts of background information, which is especially true for viruses with small genomes. Enormous sequencing depth can be necessary to compile sufficient information for identification of a certain pathogen. Generic HTS combining with in-solution capture enrichment can markedly increase the sensitivity for virus detection in complex diagnostic samples.

METHODS

A virus panel based on the principle of biotinylated RNA baits was developed for specific capture enrichment of epizootic and zoonotic viruses (VirBaits). The VirBaits set was supplemented by a SARS-CoV-2 predesigned bait set for testing recent SARS-CoV-2-positive samples. Libraries generated from complex samples were sequenced via generic HTS (without enrichment) and afterwards enriched with the VirBaits set. For validation, an internal proficiency test for emerging epizootic and zoonotic viruses (African swine fever virus, Ebolavirus, Marburgvirus, Nipah henipavirus, Rift Valley fever virus) was conducted.

RESULTS

The VirBaits set consists of 177,471 RNA baits (80-mer) based on about 18,800 complete viral genomes targeting 35 epizootic and zoonotic viruses. In all tested samples, viruses with both DNA and RNA genomes were clearly enriched ranging from about 10-fold to 10,000-fold for viruses including distantly related viruses with at least 72% overall identity to viruses represented in the bait set. Viruses showing a lower overall identity (38% and 46%) to them were not enriched but could nonetheless be detected based on capturing conserved genome regions. The internal proficiency test supports the improved virus detection using the combination of HTS plus targeted enrichment but also points to the risk of cross-contamination between samples.

CONCLUSIONS

The VirBaits approach showed a high diagnostic performance, also for distantly related viruses. The bait set is modular and expandable according to the favored diagnostics, health sector, or research question. The risk of cross-contamination needs to be taken into consideration. The application of the RNA-baits principle turned out to be user friendly, and even non-experts can easily use the VirBaits workflow. The rapid extension of the established VirBaits set adapted to actual outbreak events is possible as shown for SARS-CoV-2. Video abstract.

Proficiency Testing of Metagenomics-Based Detection of Food-Borne Pathogens Using a Complex Artificial Sequencing Dataset

Metagenomics-based high-throughput sequencing (HTS) enables comprehensive detection of all species comprised in a sample with a single assay and is becoming a standard method for outbreak investigation. However, unlike real-time PCR or serological assays, HTS datasets generated for pathogen detection do not easily provide yes/no answers. Rather, results of the taxonomic read assignment need to be assessed by trained personnel to gain information thereof. Proficiency tests are important instruments of validation, harmonization, and standardization. Within the European Union funded project COMPARE [COllaborative Management Platform for detection and Analyses of (Re-) emerging and foodborne outbreaks in Europe], we conducted a proficiency test to scrutinize the ability to assess diagnostic metagenomics data. An artificial dataset resembling shotgun sequencing of RNA from a sample of contaminated trout was provided to 12 participants with the request to provide a table with per-read taxonomic assignments at species level and a report with a summary and assessment of their findings, considering different categories like pathogen, background, or contaminations. Analysis of the read assignment tables showed that the software used reliably classified the reads taxonomically overall. However, usage of incomplete reference databases or inappropriate data pre-processing caused difficulties. From the combination of the participants' reports with their read assignments, we conclude that, although most species were detected, a number of important taxa were not or not correctly categorized. This implies that knowledge of and awareness for potentially dangerous species and contaminations need to be improved, hence, capacity building for the interpretation of diagnostic metagenomics datasets is necessary.

A Practical Method to Implement Strain-Level Metagenomics-Based Foodborne Outbreak Investigation and Source Tracking in Routine

The management of a foodborne outbreak depends on the rapid and accurate identification of the responsible food source. Conventional methods based on isolation of the pathogen from the food matrix and target-specific real-time polymerase chain reactions (qPCRs) are used in routine. In recent years, the use of whole genome sequencing (WGS) of bacterial isolates has proven its value to collect relevant information for strain characterization as well as tracing the origin of the contamination by linking the food isolate with the patient's isolate with high resolution. However, the isolation of a bacterial pathogen from food matrices is often time-consuming and not always successful. Therefore, we aimed to improve outbreak investigation by developing a method that can be implemented in reference laboratories to characterize the pathogen in the food vehicle without its prior isolation and link it back to human cases. We tested and validated a shotgun metagenomics approach by spiking food pathogens in specific food matrices using the Shiga toxin-producing Escherichia coli (STEC) as a case study. Different DNA extraction kits and enrichment procedures were investigated to obtain the most practical workflow. We demonstrated the feasibility of shotgun metagenomics to obtain the same information as in ISO/TS 13136:2012 and WGS of the isolate in parallel by inferring the genome of the contaminant and characterizing it in a shorter timeframe. This was achieved in food samples containing different E. coli strains, including a combination of different STEC strains. For the first time, we also managed to link individual strains from a food product to isolates from human cases, demonstrating the power of shotgun metagenomics for rapid outbreak investigation and source tracking.

Mass Die-Off of Saiga Antelopes, Kazakhstan, 2015

In 2015, a mass die-off of ≈200,000 saiga antelopes in central Kazakhstan was caused by hemorrhagic septicemia attributable to the bacterium Pasteurella multocida serotype B. Previous analyses have indicated that environmental triggers associated with weather conditions, specifically air moisture and temperature in the region of the saiga antelope calving during the 10-day period running up to the event, were critical to the proliferation of latent bacteria and were comparable to conditions accompanying historically similar die-offs in the same areas. We investigated whether additional viral or bacterial pathogens could be detected in samples from affected animals using 3 different high-throughput sequencing approaches. We did not identify pathogens associated with commensal bacterial opportunisms in blood, kidney, or lung samples and thus concluded that P. multocida serotype B was the primary cause of the disease.

Long-read sequencing in deciphering human genetics to a greater depth

Through four decades' development, DNA sequencing has inched into the era of single-molecule sequencing (SMS), or the third-generation sequencing (TGS), as represented by two distinct technical approaches developed independently by Pacific Bioscience (PacBio) and Oxford Nanopore Technologies (ONT). Historically, each generation of sequencing technologies was marked by innovative technological achievements and novel applications. Long reads (LRs) are considered as the most advantageous feature of SMS shared by both PacBio and ONT to distinguish SMS from next-generation sequencing (NGS, or the second-generation sequencing) and Sanger sequencing (the first-generation sequencing). Long reads overcome the limitations of NGS and drastically improves the quality of genome assembly. Besides, ONT also contributes several unique features including ultra-long reads (ULRs) with read length above 300 kb and some close to 1 million bp, direct RNA sequencing and superior portability as made possible by pocket-sized MinION sequencer. Here, we review the history of DNA sequencing technologies and associated applications, with a special focus on the advantages as well as the limitations of ULR sequencing in genome assembly.

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.

Surveillance and Diagnosis of West Nile Virus in the Face of Flavivirus Cross-Reactivity

West Nile Virus (WNV) is an arthropod-borne flavivirus whose zoonotic cycle includes both mosquitoes and birds as amplifiers and humans and horses as dead-end hosts. In recent years WNV has been spreading globally and is currently endemic in Africa, The Middle East, India, Australia, central and southern Europe, and the Americas. Integrated surveillance schemes and environmental data aim to detect viral circulation and reduce the risk of infection for the human population emphasizing the critical role for One Health principles in public health. Approximately 20% of WNV infected patients develop West Nile Fever while in less than 1%, infection results in West Nile Neurological Disease. Currently, the diagnosis of WNV infection is primarily based on serology, since molecular identification of WNV RNA is unreliable due to the short viremia. The recent emergence of Zika virus epidemic in America and Asia has added another layer of complexity to WNV diagnosis due to significant cross-reactivity between several members of the Flaviviridae family such as Zika, dengue, Usutu, and West Nile viruses. Diagnosis is especially challenging in persons living in regions with flavivirus co-circulation as well as in travelers from WNV endemic countries traveling to Zika or dengue infected areas or vise-versa. Here, we review the recent studies implementing WNV surveillance of mosquitoes and birds within the One Health initiative. Furthermore, we discuss the utility of novel molecular methods, alongside traditional molecular and serological methods, in WNV diagnosis and epidemiological research.

A Versatile Sample Processing Workflow for Metagenomic Pathogen Detection

Metagenomics is currently the only generic method for pathogen detection. Starting from RNA allows the assessment of the whole sample community including RNA viruses. Here we present our modular concerted protocol for sample processing for diagnostic metagenomics analysis of human, animal, and food samples. The workflow does not rely on dedicated amplification steps at any stage in the process and, in contrast to published methods, libraries prepared accordingly will yield only minute amounts of unclassifiable reads. We confirmed the performance of the approach using a spectrum of pathogen/matrix-combinations showing it has the potential to become a commonly usable analytical framework.

Usefulness of metagenomic analysis in differential diagnosis for pyoderma gangrenosum

Pyoderma gangrenosum (PG) is a rare ulcerative inflammatory dermatosis easily confused with wound infection following surgery. There have been seven case reports of PG occurring after total knee arthroplasty (TKA), all of which used routine tissue culture for differential diagnosis. Notably, all previous cases involved delayed diagnosis. We report a case of PG after TKA where we used shotgun metagenomics for differential diagnosis. Metagenomic analysis is a new method that can be used for pathogen detection; it is fast and sensitive, compared with traditional culture. Early application of metagenomic analysis in cases of suspicious wound infection after surgery can detect the pathogen of the infection for target therapy; it can also exclude infection for differential diagnosis of non-infectious diseases, such as autoimmune disorders. This case is presented to support the use of metagenomic analysis by surgeons and physicians for early and rapid differential diagnosis in patients who exhibit postoperative wound infections.

Novel viruses in birds: Flying through the roof or is a cage needed?

Emerging viral diseases continue to have a major global impact on human beings and animals. To be able to take adequate measures in case of an outbreak of an emerging disease, rapid detection of the causative agent is a crucial first step. In this review, various aspects of virus discovery are discussed, with a special focus on recently discovered viruses in birds. Novel viruses with a potential major impact have been discovered in domestic and wild bird species in recent years using various virus discovery methods. Only a few studies report the detection of novel viruses in endangered bird species, although increased knowledge about viruses circulating in these species is important. Additional studies focusing on the exact role of a novel virus in disease and on the impact of a novel virus on bird populations are often lacking. Intensive collaboration between different disciplines is needed to obtain useful information about the role of these novel viruses.

The Expanding Field of Mammalian Astroviruses: Opportunities and Challenges in Clinical Virology

Astroviruses are best known as being one of the leading causes of diarrhea in infants and were first described in this context in 1975. In its first years, astrovirus research was mainly restricted to electron microscopy and serology studies. The ability to culture some of these viruses in vitro allowed a first consequent step forward, especially at the molecular level. Since the emergence of more powerful genetic methods, though, the face of this research field has dramatically changed and evolved. From the exponential number of discoveries of new astrovirus strains in the most varied of animal species to their association with atypical diseases, these viruses revealed a lot of surprises, and many more are probably still waiting to be uncovered. This chapter summarizes the most important knowledge about astroviruses and discusses the implication of the latest findings in this area of research.