97 research outputs found

    PP-235 Analysis of clinical features of 70 adult patients with varicella

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    Analysing the genomic data of pathogens with the help of next-generation sequencing (NGS) is an increasingly important part of disease outbreak investigations and helps guide responses. While this technology has already been successfully employed to elucidate and control disease outbreaks, wider implementation of NGS also depends on its cost-effectiveness. COMPARE - short for 'Collaborative Management Platform for detection and Analyses of (Re-) emerging and foodborne outbreaks' - is a major project, funded by the European Union, to develop a global platform for sharing and analysing NGS data and thereby improve the rapid identification, containment and mitigation of emerging infectious diseases and foodborne outbreaks. This article introduces the project and presents the results of a review of the literature, composed of previous relevant cost-benefit and cost-effectiveness analyses. The authors also outline the implications for a methodological framework to assess the cost- effectiveness of COMPARE and similar systems

    Sources of antibiotic resistance: zoonotic, human, environment

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    Antibiotic resistance is a global problem that must be managed under the One Health perspective. Retrospectively, it is assumed that microbial populations able to cope with compounds with antimicrobial activity and susceptible bacteria lived in equilibrium for a thousand years. This situation would change in the middle 1940s of the twentieth century when one of the most important revolutions of modern medicine started - the use of a natural antimicrobial compound, the penicillin, to treat infectious bacterial diseases. Over the years, the massive use of antibiotics in human and animal medicine, as well as in animal production for both growth promotion and infection prophylaxis/metaphylaxis, accelerated and shaped one of the most successful evolutionary case studies. As a result of an impressive combination of genome and community dynamics, bacteria with acquired antibiotic resistance are nowadays widespread across different environmental compartments (water, soil, wildlife) as well as in the human food chain (poultry, livestock, aquaculture, produce). Hence, the evolutionary success of these bacteria turned to represent a major threat to the human health. This review discusses some of the drivers and paths of antibiotic resistance dissemination across zoonotic, human, and environmental sources.info:eu-repo/semantics/acceptedVersio

    Metagenomics-based proficiency test of smoked salmon spiked with a mock community

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    An inter-laboratory proficiency test was organized to assess the ability of participants to perform shotgun metagenomic sequencing of cold smoked salmon, experimentally spiked with a mock community composed of six bacteria, one parasite, one yeast, one DNA, and two RNA viruses. Each participant applied its in-house wet-lab workflow(s) to obtain the metagenomic dataset(s), which were then collected and analyzed using MG-RAST. A total of 27 datasets were analyzed. Sample pre-processing, DNA extraction protocol, library preparation kit, and sequencing platform, influenced the abundance of specific microorganisms of the mock community. Our results highlight that despite differences in wet-lab protocols, the reads corresponding to the mock community members spiked in the cold smoked salmon, were both detected and quantified in terms of relative abundance, in the metagenomic datasets, proving the suitability of shotgun metagenomic sequencing as a genomic tool to detect microorganisms belonging to different domains in the same food matrix. The implementation of standardized wet-lab protocols would highly facilitate the comparability of shotgun metagenomic sequencing dataset across laboratories and sectors. Moreover, there is a need for clearly defining a sequencing reads threshold, to consider pathogens as detected or undetected in a food sample

    Proficiency testing of virus diagnostics based on bioinformatics analysis of simulated in silico high-throughput sequencing data sets

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    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

    The COMPARE Data Hubs

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    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

    Setting a baseline for global urban virome surveillance in sewage

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    The rapid development of megacities, and their growing connectedness across the world is becoming a distinct driver for emerging disease outbreaks. Early detection of unusual disease emergence and spread should therefore include such cities as part of risk-based surveillance. A catch-all metagenomic sequencing approach of urban sewage could potentially provide an unbiased insight into the dynamics of viral pathogens circulating in a community irrespective of access to care, a potential which already has been proven for the surveillance of poliovirus. Here, we present a detailed characterization of sewage viromes from a snapshot of 81 high density urban areas across the globe, including in-depth assessment of potential biases, as a proof of concept for catch-all viral pathogen surveillance. We show the ability to detect a wide range of viruses and geographical and seasonal differences for specific viral groups. Our findings offer a cross-sectional baseline for further research in viral surveillance from urban sewage samples and place previous studies in a global perspective
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