The Transcriptional Landscape of Marek’s Disease Virus in Primary Chicken B Cells Reveals Novel Splice Variants and Genes

Marek’s disease virus (MDV) is an oncogenic alphaherpesvirus that infects chickens and poses a serious threat to poultry health. In infected animals, MDV efficiently replicates in B cells in various lymphoid organs. Despite many years of research, the viral transcriptome in primary target cells of MDV remained unknown. In this study, we uncovered the transcriptional landscape of the very virulent RB1B strain and the attenuated CVI988/Rispens vaccine strain in primary chicken B cells using high-throughput RNA-sequencing. Our data confirmed the expression of known genes, but also identified a novel spliced MDV gene in the unique short region of the genome. Furthermore, de novo transcriptome assembly revealed extensive splicing of viral genes resulting in coding and non-coding RNA transcripts. A novel splicing isoform of MDV UL15 could also be confirmed by mass spectrometry and RT-PCR. In addition, we could demonstrate that the associated transcriptional motifs are highly conserved and closely resembled those of the host transcriptional machinery. Taken together, our data allow a comprehensive re-annotation of the MDV genome with novel genes and splice variants that could be targeted in further research on MDV replication and tumorigenesis

Restoration of peatlands and greenhouse gas balances

In this chapter the impact of peatland restoration on greenhouse gas fluxes is discussed based on a literature review. Casestudies are presented covering different peatland types, different regions and different starting conditions

Compellingly high SARS-CoV-2 susceptibility of Golden Syrian hamsters suggests multiple zoonotic infections of pet hamsters during the COVID-19 pandemic

Golden Syrian hamsters (Mesocricetus auratus) are used as a research model for severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2). Millions of Golden Syrian hamsters are also kept as pets in close contact to humans. To determine the minimum infective dose (MID) for assessing the zoonotic transmission risk, and to define the optimal infection dose for experimental studies, we orotracheally inoculated hamsters with SARS-CoV-2 doses from 1 * 105 to 1 * 10-4 tissue culture infectious dose 50 (TCID50). Body weight and virus shedding were monitored daily. 1 * 10-3 TCID50 was defined as the MID, and this was still sufficient to induce virus shedding at levels up to 102.75 TCID50/ml, equaling the estimated MID for humans. Virological and histological data revealed 1 * 102 TCID50 as the optimal dose for experimental infections. This compelling high susceptibility leading to productive infections in Golden Syrian hamsters must be considered as a potential source of SARS-CoV-2 infection for humans that come into close contact with pet hamsters

Mass Die-Off of Saiga Antelopes, Kazakhstan, 2015

In 2015, a mass die-off of ≈200,000 saiga antelope 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

Defining objective clusters for rabies virus sequences using affinity propagation clustering

Rabies is caused by lyssaviruses, and is one of the oldest known zoonoses. In recent years, more than 21,000 nucleotide sequences of rabies viruses (RABV), from the prototype species rabies lyssavirus, have been deposited in public databases. Subsequent phylogenetic analyses in combination with metadata suggest geographic distributions of RABV. However, these analyses somewhat experience technical difficulties in defining verifiable criteria for cluster allocations in phylogenetic trees inviting for a more rational approach. Therefore, we applied a relatively new mathematical clustering algorythm named ‘affinity propagation clustering’ (AP) to propose a standardized sub-species classification utilizing full-genome RABV sequences. Because AP has the advantage that it is computationally fast and works for any meaningful measure of similarity between data samples, it has previously been applied successfully in bioinformatics, for analysis of microarray and gene expression data, however, cluster analysis of sequences is still in its infancy. Existing (516) and original (46) full genome RABV sequences were used to demonstrate the application of AP for RABV clustering. On a global scale, AP proposed four clusters, i.e. New World cluster, Arctic/Arctic-like, Cosmopolitan, and Asian as previously assigned by phylogenetic studies. By combining AP with established phylogenetic analyses, it is possible to resolve phylogenetic relationships between verifiably determined clusters and sequences. This workflow will be useful in confirming cluster distributions in a uniform transparent manner, not only for RABV, but also for other comparative sequence analyses

Recognition of COVID-19 with occupational origin: a comparison between European countries

Objectives This study aims to present an overview of the formal recognition of COVID-19 as occupational disease (OD) or injury (OI) across Europe. Methods A COVID-19 questionnaire was designed by a task group within COST-funded OMEGA-NET and sent to occupational health experts of 37 countries in WHO European region, with a last update in April 2022. Results The questionnaire was filled out by experts from 35 countries. There are large differences between national systems regarding the recognition of OD and OI: 40% of countries have a list system, 57% a mixed system and one country an open system. In most countries, COVID-19 can be recognised as an OD (57%). In four countries, COVID-19 can be recognised as OI (11%) and in seven countries as either OD or OI (20%). In two countries, there is no recognition possible to date. Thirty-two countries (91%) recognise COVID-19 as OD/OI among healthcare workers. Working in certain jobs is considered proof of occupational exposure in 25 countries, contact with a colleague with confirmed infection in 19 countries, and contact with clients with confirmed infection in 21 countries. In most countries (57%), a positive PCR test is considered proof of disease. The three most common compensation benefits for COVID-19 as OI/OD are disability pension, treatment and rehabilitation. Long COVID is included in 26 countries. Conclusions COVID-19 can be recognised as OD or OI in 94% of the European countries completing this survey, across different social security and embedded occupational health systems.This publication is based on work from COST Action CA16216 (OMEGA-NET), supported by COST (European Cooperation in Science and Technology)

The COMPARE Data Hubs

Data sharing enables research communities to exchange findings and build upon the knowledge that arises from their discoveries. Areas of public and animal health as well as food safety would benefit from rapid data sharing when it comes to emergencies. However, ethical, regulatory and institutional challenges, as well as lack of suitable platforms which provide an infrastructure for data sharing in structured formats, often lead to data not being shared or at most shared in form of supplementary materials in journal publications. Here, we describe an informatics platform that includes workflows for structured data storage, managing and pre-publication sharing of pathogen sequencing data and its analysis interpretations with relevant stakeholders

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