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.

Metagenomics for broad and improved parasite detection: a proof-of-concept study using swine faecal samples.

Efficient and reliable identification of emerging pathogens is crucial for the design and implementation of timely and proportionate control strategies. This is difficult if the pathogen is so far unknown or only distantly related with known pathogens. Diagnostic metagenomics - an undirected, broad and sensitive method for the efficient identification of pathogens - was frequently used for virus and bacteria detection, but seldom applied to parasite identification.

Proficiency Testing of Virus Diagnostics Based on Bioinformatics Analysis of Simulated 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 [llaborative anagement latform for Detection and nalyses of (e-)emerging and Foodborne Outbreaks in urope] virus proficiency test.

LVQ-KNN: Composition-based DNA/RNA binning of short nucleotide sequences utilizing a prototype-based k-nearest neighbor approach.

Unbiased sequencing is an upcoming method to gain information of the microbiome in a sample and for the detection of unrecognized pathogens. There are many software tools for a taxonomic classification of such metagenomics datasets available. Numerous of them have a satisfactory sensitivity and specificity for known organisms, but they fail if the sample contains unknown organisms, which cannot be detected by similarity-based classification employing available databases.

The Accessory Genome of Shiga Toxin-Producing Escherichia coli Defines a Persistent Colonization Type in Cattle.

Unlabelled: Shiga toxin-producing Escherichia coli (STEC) strains can colonize cattle for several months and may, thus, serve as gene reservoirs for the genesis of highly virulent zoonotic enterohemorrhagic E. coli (EHEC). Attempts to reduce the human risk for acquiring EHEC infections should include strategies to control such STEC strains persisting in cattle.