De novo identification of viral pathogens from cell culture hologenomes

A new strain of white spot syndrome virus affecting Litopenaeus vannamei in Indian shrimp farms

White spot syndrome virus (WSSV)-infected shrimp samples collected from grow-out ponds located at Nellore, Andhra Pradesh, India, showed WSSV negative and positive by PCR using primer sets specific to ORF119 and VP28 gene of WSSV, respectively. This indicated the deletion of genetic fragments in the genome of WSSV. The WSSV isolate along with lab strain of WSSV was subjected to next-generation sequencing. The sequence analysis revealed a deletion of 13,170 bp at five positions in the genome of WSSV-NS (new strain) relative to WSSV-TH and WSSV-LS (lab strain). The PCR analysis using the ORF's specific primer sets revealed the complete deletion of 10 ORFs in the genome of WSSV-NS strain. The primer set was designed based on sequence covering ORF161/162/163 to amplify a product of 2,748 bp for WSSV-LS and 402 bp for WSSV-NS. Our surveillance programme carried out since 2002 revealed the replacement of WSSV-LS by WSSV-NS in Indian shrimp culture system.

Sensitive detection of viral transcripts in human tumor transcriptomes

In excess of % of human cancer incidents have a viral cofactor. Epidemiological studies of idiopathic human cancers indicate that additional tumor viruses remain to be discovered. Recent advances in sequencing technology have enabled systematic screenings of human tumor transcriptomes for viral transcripts. However, technical problems such as low abundances of viral transcripts in large volumes of sequencing data, viral sequence divergence, and homology between viral and human factors significantly confound identification of tumor viruses. We have developed a novel computational approach for detecting viral transcripts in human cancers that takes the aforementioned confounding factors into account and is applicable to a wide variety of viruses and tumors. We apply the approach to conducting the first systematic search for viruses in neuroblastoma, the most common cancer in infancy. The diverse clinical progression of this disease as well as related epidemiological and virological findings are highly suggestive of a pathogenic cofactor. However, a viral etiology of neuroblastoma is currently contested. We mapped transcriptomes of neuroblastoma as well as positive and negative controls to the human and all known viral genomes in order to detect both known and unknown viruses. Analysis of controls, comparisons with related methods, and statistical estimates demonstrate the high sensitivity of our approach. Detailed investigation of putative viral transcripts within neuroblastoma samples did not provide evidence for the existence of any known human viruses. Likewise, de-novo assembly and analysis of chimeric transcripts did not result in expression signatures associated with novel human pathogens. While confounding factors such as sample dilution or viral clearance in progressed tumors may mask viral cofactors in the data, in principle, this is rendered less likely by the high sensitivity of our approach and the number of biological replicates analyzed. Therefore, our results suggest that frequent viral cofactors of metastatic neuroblastoma are unlikely.

Many human cancers are caused by infections with tumor viruses and identification of these pathogens is considered a critical contribution to cancer prevention. Deep sequencing enables us to systematically investigate viral nucleotide signatures in order to either verify or exclude the existence of viruses in idiopathic human cancers. We have developed Virana, a novel computational approach for identifying tumor viruses in human cancers that is applicable to a wide variety of tumors and viruses. Virana firstly addresses several important biological confounding factors that may hinder successful detection of these pathogens. We applied our approach in the first systematic search for cancer-causing viruses in metastatic neuroblastoma, the most common form of cancer in infancy. Although the heterogeneous clinical progression of this disease as well as epidemiological and virological findings are suggestive of a pathogenic cofactor, the viral etiology of neuroblastoma is currently contested. We conducted an analysis of experimental controls, comparisons with related approaches, as well as statistical analyses in order to validate our method. In spite of the high sensitivity of our approach, analyses of neuroblastoma transcriptomes did not provide evidence for the existence of any known or unknown human viruses. Our results therefore suggest that frequent viral cofactors of metastatic neuroblastoma are unlikely.

VirusFinder: software for efficient and accurate detection of viruses and their integration sites in host genomes through next generation sequencing data

Next generation sequencing (NGS) technologies allow us to explore virus interactions with host genomes that lead to carcinogenesis or other diseases; however, this effort is largely hindered by the dearth of efficient computational tools. Here, we present a new tool, VirusFinder, for the identification of viruses and their integration sites in host genomes using NGS data, including whole transcriptome sequencing (RNA-Seq), whole genome sequencing (WGS), and targeted sequencing data. VirusFinder’s unique features include the characterization of insertion loci of virus of arbitrary type in the host genome and high accuracy and computational efficiency as a result of its well-designed pipeline. The source code as well as additional data of VirusFinder is publicly available at http://bioinfo.mc.vanderbilt.edu/VirusFinder/.

Metagenomic identification of viral pathogens

The target-independent identification of viral pathogens using 'shotgun' metagenomic sequencing is an emerging approach with potentially wide applications in clinical diagnostics, public health monitoring, and viral discovery. In this approach, all viral nucleic acids present in a sample are sequenced in a random, shotgun manner. Pathogens are then identified without the prerequisite of searching for a specific viral pathogen. In this opinion article, I discuss the current state and future research directions for this emerging and disruptive technology. With further technical developments, viral metagenomics has the potential to be deployed as a powerful and widely adopted tool, transforming the way that viral disease is researched, monitored, and treated.