http://edoc.rki.de/176904/44 2026-08-13T15:49:36Z 2026-08-13T15:49:36Z Mouchtouri, Varvara A. Verykouki, Eleni Zamfir, Dumitru Hadjipetris, Christos Lewis, Hannah C. Hadjichristodoulou, Christos EU SHIPSAN ACT partnership http://edoc.rki.de/176904/13821 2026-08-13T15:27:26Z 2017-11-09T00:00:00Z

Gastroentritis outbreaks on cruise ships: contributing factors and thresholds for early outbreak detection Mouchtouri, Varvara A.; Verykouki, Eleni; Zamfir, Dumitru; Hadjipetris, Christos; Lewis, Hannah C.; Hadjichristodoulou, Christos; EU SHIPSAN ACT partnership

2017-11-09T00:00:00Z Nadon, Celine van Walle, Ivo Gerner-Schmidt, Peter Campos, Josefinaa Chinen, Isabel Concepcion-Acevedo, Jeniffer Gilpin, Brent Smith, Anthony M. Kai Man, J. Kam Perez, Enrique Trees, Eija Kubota, Kristy Takkinen, Johana Møller Nielsen, Eva Carleton, Heather FWD-NEXT Expert Panel http://edoc.rki.de/176904/13820 2026-08-13T15:27:27Z 2017-06-08T00:00:00Z

PulseNet International: Vision for th implementation of whole genome sequencing (WGS) for global food-borne disease surveillance Nadon, Celine; van Walle, Ivo; Gerner-Schmidt, Peter; Campos, Josefinaa; Chinen, Isabel; Concepcion-Acevedo, Jeniffer; Gilpin, Brent; Smith, Anthony M.; Kai Man, J. Kam; Perez, Enrique; Trees, Eija; Kubota, Kristy; Takkinen, Johana; Møller Nielsen, Eva; Carleton, Heather; FWD-NEXT Expert Panel PulseNet International is a global network dedicated to laboratory-based surveillance for food-borne diseases. The network comprises the national and regional laboratory networks of Africa, Asia Pacific, Canada, Europe, Latin America and the Caribbean, the Middle East, and the United States. The PulseNet International vision is the standardised use of whole genome sequencing (WGS) to identify and subtype food-borne bacterial pathogens worldwide, replacing traditional methods to strengthen preparedness and response, reduce global social and economic disease burden, and save lives. To meet the needs of real-time surveillance, the PulseNet International network will standardise subtyping via WGS using whole genome multilocus sequence typing (wgMLST), which delivers sufficiently high resolution and epidemiological concordance, plus unambiguous nomenclature for the purposes of surveillance. Standardised protocols, vali- dation studies, quality control programmes, database and nomenclature development, and training should support the implementation and decentralisation of WGS. Ideally, WGS data collected for surveillance purposes should be publicly available, in real time where possible, respecting data protection policies. WGS data are suitable for surveillance and outbreak purposes and for answering scientific questions pertaining to source attribution, antimicrobial resistance, transmission patterns, and virulence, which will further enable the protection and improvement of public health with respect to food-borne disease

2017-06-08T00:00:00Z Piro, Victor C. Matschkowski, Marcel Renard, Bernhard Y. http://edoc.rki.de/176904/13819 2026-08-13T14:57:25Z 2017-08-14T00:00:00Z

MetaMeta: integrating metagenome analysis tools to improve taxonomic profiling Piro, Victor C.; Matschkowski, Marcel; Renard, Bernhard Y. Background Many metagenome analysis tools are presently available to classify sequences and profile environmental samples. In particular, taxonomic profiling and binning methods are commonly used for such tasks. Tools available among these two categories make use of several techniques, e.g., read mapping, k-mer alignment, and composition analysis. Variations on the construction of the corresponding reference sequence databases are also common. In addition, different tools provide good results in different datasets and configurations. All this variation creates a complicated scenario to researchers to decide which methods to use. Installation, configuration and execution can also be difficult especially when dealing with multiple datasets and tools. Results We propose MetaMeta: a pipeline to execute and integrate results from metagenome analysis tools. MetaMeta provides an easy workflow to run multiple tools with multiple samples, producing a single enhanced output profile for each sample. MetaMeta includes a database generation, pre-processing, execution, and integration steps, allowing easy execution and parallelization. The integration relies on the co-occurrence of organisms from different methods as the main feature to improve community profiling while accounting for differences in their databases. Conclusions In a controlled case with simulated and real data, we show that the integrated profiles of MetaMeta overcome the best single profile. Using the same input data, it provides more sensitive and reliable results with the presence of each organism being supported by several methods. MetaMeta uses Snakemake and has six pre-configured tools, all available at BioConda channel for easy installation (conda install -c bioconda metameta). The MetaMeta pipeline is open-source and can be downloaded at: https://gitlab.com/rki_bioinformatics.

2017-08-14T00:00:00Z Scheidt-Nave, Christa Neuhauser, Hannelore http://edoc.rki.de/176904/13818 2026-08-13T14:57:24Z 2017-12-01T00:00:00Z

In Reply Scheidt-Nave, Christa; Neuhauser, Hannelore

2017-12-01T00:00:00Z