Analysis of Viral Genomes Using Next-generation Sequencing

Bastian Beggel & Sven-Eric Schelhorn

Analysis of Viral Genomes Using Next-generation Sequencing

Research on viral infections is heavily dependent on available genome sequences of both the virus and its human host. These genome sequences provide the basis for understanding the complex molecular interplay between the pathogen and the patient, knowledge that is crucial for both drug development and therapy optimization. The advent of next-generation sequencing technologies resulted in a dramatic drop in cost and increase in throughput of genome sequencing. However, the computational and methodological difficulties regarding storage, analysis, and interpretation of the sequence data are considerable. It has recently become clear that the main bottleneck hindering advances in high-throughput genomic research is not the limited availability of patient samples or sequencing machines, but instead the lack of automated tools and trained bioinformaticians able to analyze this deluge of data.

Standardizing viral sequence analysis with Virana

The situation is further complicated by the fact that viral genomes differ from the genomes of multicellular organisms such as humans in their very high evolutionary rate and intra-species diversity, resulting in an especially complex genotype. These peculiarities compromise the suitability of traditional tools and analysis methods developed for the analysis of the human genome to study infections by viruses. We aim to fill this methodological gap by developing “Virana”, a software package and associated web service for viral next-generation sequence analysis. Virana is specifically tailored to the analysis of clinical data and takes the complex viral genotype as well as the longitudinal character of antiviral therapies into account. Analyses performed with the Virana web service can be conducted by non-specialists and are both highly scalable and replicable. Additionally, analysis workflows and results can conveniently be shared over the Internet, encouraging communication and collaboration.

Sequence dynamics of the hepatitis C virus

At the Hospital of the University of Frankfurt, Virana is currently employed in a clinical setting to model the intrahost evolution of the hepatitis C virus. The characterization of the highly complex genotype of this virus is crucial for studying novel resistance mechanisms that the virus evolves to escape antiviral drug regimens. The unique methods offered by Virana enable researchers to statistically infer genotypic markers, such as minority sequence variants and genomic haplotypes, from the sequence data. When tracked over the course of an infection and combined with phenotypic variables such as therapy success, these markers can be used to support further clinical decision-making. Results of such analyses can then be incorporated into our software geno2pheno[hcv], a free Web service that aids medical doctors by predicting drug resistance of viruses derived from patient samples, thereby translating personalized genomics into clinical practice.

Output of the geno2pheno[hcv] web service

Modification of the natural progression of chronic hepatitis B

Next-generation sequencing is also used to analyze the complex interaction of the hepatitis B virus with the host’s immune system on the basis of the viral genome. The natural progression of a chronic hepatitis B infection consists of four phases. The immune-tolerant phase and the inactive phase are characterized by a favorable progression of the infection, whereas patients in the immuneactive and the reactive phases are at high risk of developing irreversible liver damage in the medium term. Despite intensive research, relatively little is known about the determinants that cause phase transitions, e.g. from the inactive to the reactive phase. Together with our collaboration partners from the university hospital in Düsseldorf, we analyze the entire viral population within a host of multiple patients at several characteristic points in time. This will eventually provide indicators to characterize and predict phase transitions. By these means it may be possible to prevent deleterious phase transitions in an early stage using antiviral drugs, which would avoid or at least delay fatal progression of a chronic hepatitis B infection using as little medication as possible.