Tick-borne encephalitis virus (TBEV) prevalence in field-collected ticks (Ixodes ricinus) and phylogenetic, structural and virulence analysis in a TBE high-risk endemic area in southwestern Germany.

BACKGROUND: Tick-borne encephalitis (TBE) is the most common viral CNS infection with incidences much higher than all other virus infections together in many risk areas of central and eastern Europe. The Odenwald Hill region (OWH) in southwestern Germany is classified as a TBE risk region and frequent case numbers but also more severe infections have been reported within the past decade. The objective of the present study was to survey the prevalence of tick-borne encephalitis virus (TBEV) in Ixodes ricinus and to associate TBEV genetic findings with TBE infections in the OWH. METHODS: Ticks were collected by the flagging methods supported by a crowdsourcing project implementing the interested public as collectors to cover completely and collect randomly a 3532 km2 area of the OWH TBE risk region. Prevalence of TBEV in I. ricinus was analysed by reversed transcription quantitative real-time PCR. Phylogeographic analysis was performed to classify OWH TBEV isolates within a European network of known TBEV strains. Mutational sequence analysis including 3D modelling of envelope protein pE was performed and based on a clinical database, a spatial association of TBE case frequency and severity was undertaken. RESULTS: Using the crowd sourcing approach we could analyse a total of 17,893 ticks. The prevalence of TBEV in I. ricinus in the OWH varied, depending on analysed districts from 0.12% to 0% (mean 0.04%). Calculated minimum infection rate (MIR) was one decimal power higher. All TBEV isolates belonged to the European subtype. Sequence analysis revealed a discontinuous segregation pattern of OWH isolates with two putative different lineages and a spatial association of two isolates with increased TBE case numbers as well as exceptional severe to fatal infection courses. CONCLUSIONS: TBEV prevalence within the OWH risk regions is comparatively low which is probably due to our methodological approach and may more likely reflect prevalence of natural TBEV foci. As for other European regions, TBEV genetics show a discontinuous phylogeny indicating among others an association with bird migration. Mutations within the pE gene are associated with more frequent, severe and fatal TBE infections in the OWH risk region.

Genomic footprints of activated telomere maintenance mechanisms in cancer.

Cancers require telomere maintenance mechanisms for unlimited replicative potential. They achieve this through TERT activation or alternative telomere lengthening associated with ATRX or DAXX loss. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we dissect whole-genome sequencing data of over 2500 matched tumor-control samples from 36 different tumor types aggregated within the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium to characterize the genomic footprints of these mechanisms. While the telomere content of tumors with ATRX or DAXX mutations (ATRX/DAXXtrunc) is increased, tumors with TERT modifications show a moderate decrease of telomere content. One quarter of all tumor samples contain somatic integrations of telomeric sequences into non-telomeric DNA. This fraction is increased to 80% prevalence in ATRX/DAXXtrunc tumors, which carry an aberrant telomere variant repeat (TVR) distribution as another genomic marker. The latter feature includes enrichment or depletion of the previously undescribed singleton TVRs TTCGGG and TTTGGG, respectively. Our systematic analysis provides new insight into the recurrent genomic alterations associated with telomere maintenance mechanisms in cancer.

TelomereHunter - in silico estimation of telomere content and composition from cancer genomes.

BACKGROUND: Establishment of telomere maintenance mechanisms is a universal step in tumor development to achieve replicative immortality. These processes leave molecular footprints in cancer genomes in the form of altered telomere content and aberrations in telomere composition. To retrieve these telomere characteristics from high-throughput sequencing data the available computational approaches need to be extended and optimized to fully exploit the information provided by large scale cancer genome data sets. RESULTS: We here present TelomereHunter, a software for the detailed characterization of telomere maintenance mechanism footprints in the genome. The tool is implemented for the analysis of large cancer genome cohorts and provides a variety of diagnostic diagrams as well as machine-readable output for subsequent analysis. A novel key feature is the extraction of singleton telomere variant repeats, which improves the identification and subclassification of the alternative lengthening of telomeres phenotype. We find that whole genome sequencing-derived telomere content estimates strongly correlate with telomere qPCR measurements (r = 0.94). For the first time, we determine the correlation of in silico telomere content quantification from whole genome sequencing and whole genome bisulfite sequencing data derived from the same tumor sample (r = 0.78). An analogous comparison of whole exome sequencing data and whole genome sequencing data measured slightly lower correlation (r = 0.79). However, this is considerably improved by normalization with matched controls (r = 0.91). CONCLUSIONS: TelomereHunter provides new functionality for the analysis of the footprints of telomere maintenance mechanisms in cancer genomes. Besides whole genome sequencing, whole exome sequencing and whole genome bisulfite sequencing are suited for in silico telomere content quantification, especially if matched control samples are available. The software runs under a GPL license and is available at https://www.dkfz.de/en/applied-bioinformatics/telomerehunter/telomerehunter.html .

Gene Expression Profiling in Abdominal Aortic Aneurysms After Finite Element Rupture Risk Assessment.

PURPOSE: To investigate the association between local biomechanical rupture risk calculations from finite element analysis (FEA) and whole-genome profiling of the abdominal aortic aneurysm (AAA) wall to determine if AAA wall regions with highest and lowest estimated rupture risk show different gene expression patterns. METHODS: Six patients (mean age 74 years; all men) scheduled for open surgery to treat asymptomatic AAAs (mean diameter 55.2±3.5 mm) were recruited for the study. Rupture risk profiles were estimated by FEA from preoperative computed tomography angiography data. During surgery, AAA wall samples of ~10 mm2 were extracted from the lowest and highest rupture risk locations identified by the FEA. Twelve samples were processed for RNA extraction and subsequent whole genome expression profiling. Expression of single genes and of predefined gene groups were compared between vessel wall areas with highest and lowest predicted rupture risk. RESULTS: Normalized datasets comprised 15,079 gene transcripts with expression above background. In biopsies with high rupture risk, upregulation of 18 and downregulation of 18 genes was detected when compared to the low-risk counterpart. Global analysis of predefined gene groups revealed expression differences in genes associated with extracellular matrix (ECM) degradation (p<0.001), matrix metalloproteinase activity (p<0.001), and chemokine signaling (p<0.001). CONCLUSION: Increased expression of genes involved in degrading ECM components was present in AAA wall regions with highest biomechanical stress, supporting the thesis of mechanotransduction. More experimental studies with cooperation of multicenter vascular biobanks are necessary to understand AAA etiologies and identify further parameters of FEA model complementation.

A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing.

As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Here using tumour-normal sample pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, we conduct a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines and validation methods. We show that using PCR-free methods and increasing sequencing depth to ∼ 100 × shows benefits, as long as the tumour:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artefact-prone nature of the raw data and lack of standards for dealing with the artefacts. However, we show that, using the benchmark mutation set we have created, many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy.