Identification of Known and Novel Recurrent Viral Sequences in Data from Multiple Patients and Multiple Cancers

Metagenomic Identification of Viral Sequences in Laboratory Reagents

Metagenomic next-generation sequencing has transformed the discovery and diagnosis of infectious disease, with the power to characterise the complete 'infectome' (bacteria, viruses, fungi, parasites) of an individual host organism. However, the identification of novel pathogens has been complicated by widespread microbial contamination in commonly used laboratory reagents. Using total RNA sequencing ("metatranscriptomics") we documented the presence of contaminant viral sequences in multiple 'blank' negative control sequencing libraries that comprise a sterile water and reagent mix. Accordingly, we identified 14 viral sequences in 7 negative control sequencing libraries. As in previous studies, several circular replication-associated protein encoding (CRESS) DNA virus-like sequences were recovered in the blank control libraries, as well as contaminating sequences from the Totiviridae, Tombusviridae and Lentiviridae families of RNA virus. These data suggest that viral contamination of common laboratory reagents is likely commonplace and can comprise a wide variety of viruses.

Current challenges to virus discovery by meta-transcriptomics

Meta-transcriptomic next-generation sequencing has transformed virus discovery, dramatically expanding our knowledge of the known virosphere. Nevertheless, the use of meta-transcriptomics for virus discovery faces important challenges. As this technology becomes more widely adopted, the proportion of viral sequences in public databases with incorrect (e.g. mis-assignment of host) or limited information (e.g. lacking taxonomic classification) is likely to grow, limiting their utility in bioinformatic pipelines for virus discovery. In addition, we currently lack the bioinformatic tools that can accurately identify viruses showing little or no sequence similarity to database viruses or those that represent likely reagent contaminants. Herein, we outline some of the challenges to effective meta-transcriptomic virus discovery as well as their potential solutions.

Potential prognostic impact of EBV RNA-seq reads in gastric cancer: a reanalysis of The Cancer Genome Atlas cohort

Epstein-Barr virus (EBV)-associated gastric cancer (EBVaGC), whose prognosis remains controversial, is diagnosed by in situ hybridization of EBV-derived EBER1/2 small RNAs. In The Cancer Genome Atlas (TCGA) Stomach Adenocarcinoma (STAD) project, the EBV molecular subtype was determined through a combination of multiple next-generation sequencing methods, but not by the gold standard in situ hybridization method. This leaves unanswered questions regarding the discordance of EBV positivity detected by different approaches and the threshold of sequencing reads. Therefore, we reanalyzed the TCGA-STAD RNA sequencing (RNA-seq) dataset including 375 tumor and 32 normal samples, using our analysis pipeline. We defined a reliable threshold for EBV-derived next-generation sequencing reads by mapping them to the EBV genome with three different random arbitrary alignments. We analyzed the prognostic impact of EBV status on the histopathological subtypes of gastric cancer. EBV-positive cases identified by reanalysis comprised nearly half of the cases (49.6%) independent from infiltrating lymphocyte signatures, and showed significantly longer overall survival for adenocarcinomas of the 'not-otherwise-specified' type [P = 0.016 (log-rank test); hazard ratios (HR): 0.476; 95% CI: 0.260-0.870, P = 0.016 (Cox univariate analysis)], but shorter overall survival for the tubular adenocarcinoma type [P = 0.005 (log-rank test); HR: 3.329; 95% CI: 1.406-7.885, P = 0.006 (Cox univariate analysis)]. These results demonstrate that the EBV positivity rates were higher when determined by RNA-seq than when determined by EBER1/2 in situ hybridization. The RNA-seq-based EBV positivity demonstrated distinct results for gastric cancer prognosis depending on the histopathological subtype, suggesting its potential to be used in clinical prognoses.

DAMIAN: an open source bioinformatics tool for fast, systematic and cohort based analysis of microorganisms in diagnostic samples

We describe DAMIAN, an open source bioinformatics tool designed for the identification of pathogenic microorganisms in diagnostic samples. By using authentic clinical samples and comparing our results to those from established analysis pipelines as well as conventional diagnostics, we demonstrate that DAMIAN rapidly identifies pathogens in different diagnostic entities, and accurately classifies viral agents down to the strain level. We furthermore show that DAMIAN is able to assemble full-length viral genomes even in samples co-infected with multiple virus strains, an ability which is of considerable advantage for the investigation of outbreak scenarios. While DAMIAN, similar to other pipelines, analyzes single samples to perform classification of sequences according to their likely taxonomic origin, it also includes a tool for cohort-based analysis. This tool uses cross-sample comparisons to identify sequence signatures that are frequently present in a sample group of interest (e.g., a disease-associated cohort), but occur less frequently in control cohorts. As this approach does not require homology searches in databases, it principally allows the identification of not only known, but also completely novel pathogens. Using samples from a meningitis outbreak, we demonstrate the feasibility of this approach in identifying enterovirus as the causative agent.

Contaminating viral sequences in high-throughput sequencing viromics: a linkage study of 700 sequencing libraries

OBJECTIVES

Sample preparation for high-throughput sequencing (HTS) includes treatment with various laboratory components, potentially carrying viral nucleic acids, the extent of which has not been thoroughly investigated. Our aim was to systematically examine a diverse repertoire of laboratory components used to prepare samples for HTS in order to identify contaminating viral sequences.

METHODS

A total of 322 samples of mainly human origin were analysed using eight protocols, applying a wide variety of laboratory components. Several samples (60% of human specimens) were processed using different protocols. In total, 712 sequencing libraries were investigated for viral sequence contamination.

RESULTS

Among sequences showing similarity to viruses, 493 were significantly associated with the use of laboratory components. Each of these viral sequences had sporadic appearance, only being identified in a subset of the samples treated with the linked laboratory component, and some were not identified in the non-template control samples. Remarkably, more than 65% of all viral sequences identified were within viral clusters linked to the use of laboratory components.

CONCLUSIONS

We show that high prevalence of contaminating viral sequences can be expected in HTS-based virome data and provide an extensive list of novel contaminating viral sequences that can be used for evaluation of viral findings in future virome and metagenome studies. Moreover, we show that detection can be problematic due to stochastic appearance and limited non-template controls. Although the exact origin of these viral sequences requires further research, our results support laboratory-component-linked viral sequence contamination of both biological and synthetic origin.

A virome-wide clonal integration analysis platform for discovering cancer viral etiology

Oncoviral infection is responsible for 12%–15% of cancer in humans. Convergent evidence from epidemiology, pathology, and oncology suggests that new viral etiologies for cancers remain to be discovered. Oncoviral profiles can be obtained from cancer genome sequencing data; however, widespread viral sequence contamination and noncausal viruses complicate the process of identifying genuine oncoviruses. Here, we propose a novel strategy to address these challenges by performing virome-wide screening of early-stage clonal viral integrations. To implement this strategy, we developed VIcaller, a novel platform for identifying viral integrations that are derived from any characterized viruses and shared by a large proportion of tumor cells using whole-genome sequencing (WGS) data. The sensitivity and precision were confirmed with simulated and benchmark cancer data sets. By applying this platform to cancer WGS data sets with proven or speculated viral etiology, we newly identified or confirmed clonal integrations of hepatitis B virus (HBV), human papillomavirus (HPV), Epstein-Barr virus (EBV), and BK Virus (BKV), suggesting the involvement of these viruses in early stages of tumorigenesis in affected tumors, such as HBV in TERT and KMT2B (also known as MLL4) gene loci in liver cancer, HPV and BKV in bladder cancer, and EBV in non-Hodgkin's lymphoma. We also showed the capacity of VIcaller to identify integrations from some uncharacterized viruses. This is the first study to systematically investigate the strategy and method of virome-wide screening of clonal integrations to identify oncoviruses. Searching clonal viral integrations with our platform has the capacity to identify virus-caused cancers and discover cancer viral etiologies.

Tumour virology in the era of high-throughput genomics

With the advent of massively parallel sequencing, oncogenic viruses in tumours can now be detected in an unbiased and comprehensive manner. Additionally, new viruses or strains can be discovered based on sequence similarity with known viruses. Using this approach, the causative agent for Merkel cell carcinoma was identified. Subsequent studies using data from large collections of tumours have confirmed models built during decades of hypothesis-driven and low-throughput research, and a more detailed and comprehensive description of virus-tumour associations have emerged. Notably, large cohorts and high sequencing depth, in combination with newly developed bioinformatical techniques, have made it possible to rule out several suggested virus-tumour associations with a high degree of confidence. In this review we discuss possibilities, limitations and insights gained from using massively parallel sequencing to characterize tumours with viral content, with emphasis on detection of viral sequences and genomic integration events.This article is part of the themed issue 'Human oncogenic viruses'.

The Human Virome: Implications for Clinical Practice in Transplantation Medicine

Advances in DNA sequencing technology have provided an unprecedented opportunity to study the human virome. Transplant recipients and other immunocompromised hosts are at particular risk for developing virus-related pathology; thus, the impact of the virome on health and disease may be even more relevant in this population. Here, we discuss technical considerations in studying the human virome, the current literature on the virome in transplant recipients, and near-future applications of sequence-based findings that can further our understanding of viruses in transplantation medicine.

High diversity of picornaviruses in rats from different continents revealed by deep sequencing

Outbreaks of zoonotic diseases in humans and livestock are not uncommon, and an important component in containment of such emerging viral diseases is rapid and reliable diagnostics. Such methods are often PCR-based and hence require the availability of sequence data from the pathogen. Rattus norvegicus (R. norvegicus) is a known reservoir for important zoonotic pathogens. Transmission may be direct via contact with the animal, for example, through exposure to its faecal matter, or indirectly mediated by arthropod vectors. Here we investigated the viral content in rat faecal matter (n=29) collected from two continents by analyzing 2.2 billion next-generation sequencing reads derived from both DNA and RNA. Among other virus families, we found sequences from members of the Picornaviridae to be abundant in the microbiome of all the samples. Here we describe the diversity of the picornavirus-like contigs including near-full-length genomes closely related to the Boone cardiovirus and Theiler's encephalomyelitis virus. From this study, we conclude that picornaviruses within R. norvegicus are more diverse than previously recognized. The virome of R. norvegicus should be investigated further to assess the full potential for zoonotic virus transmission.