Accelerating surveillance and research of antimicrobial resistance - an online repository for sharing of antimicrobial susceptibility data associated with whole-genome sequences

• Published in: Microbial genomics Vol. 6; no. 5
• Main Authors: Matamoros, Sébastien, Hendriksen, Rene S, Pataki, Bálint Ármin, Pakseresht, Nima, Rossello, Marc, Silvester, Nicole, Amid, Clara, Aarestrup, Frank M, Koopmans, Marion, Cochrane, Guy, Csabai, Istvan, Lund, Ole, Schultsz, Constance, The Compare Ml-Amr Group
• Format: Journal Article
• Language: English
• Published: England Microbiology Society 01.05.2020
• Subjects: Anti-Bacterial Agents - pharmacology; Bacteria - drug effects; Bacteria - genetics; Databases, Genetic; Drug Resistance, Bacterial; High-Throughput Nucleotide Sequencing; Internet; Phenotype; Short Communication; Whole Genome Sequencing - methods; database; surveillance; antimicrobial resistance; whole-genome sequencing; data sharing
• ISSN: 2057-5858; 2057-5858
• DOI: 10.1099/mgen.0.000342

Antimicrobial resistance (AMR) is an emerging threat to modern medicine. Improved diagnostics and surveillance of resistant bacteria require the development of next-generation analysis tools and collaboration between international partners. Here, we present the 'AMR Data Hub', an online infrastructure for storage and sharing of structured phenotypic AMR data linked to bacterial whole-genome sequences. Leveraging infrastructure built by the European COMPARE Consortium and structured around the European Nucleotide Archive (ENA), the AMR Data Hub already provides an extensive data collection of more than 2500 isolates with linked genome and AMR data. Representing these data in standardized formats, we provide tools for the validation and submission of new data and services supporting search, browse and retrieval. The current collection was created through a collaboration by several partners from the European COMPARE Consortium, demonstrating the capacities and utility of the AMR Data Hub and its associated tools. We anticipate growth of content and offer the hub as a basis for future research into methods to explore and predict AMR.