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      Sequence

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      Electronic Visualisation and the Arts (EVA 2015) (EVA)

      Electronic Visualisation and the Arts

      7 & 9 July 2015

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          Abstract

          “Sequence” is a new Arts Council England funded project by artist Anna Dumitriu, in collaboration with artist/creative technologist Alex May. This biodigital installation will be exhibited for the first time at EVA 2015. The project involves the research, development and creation of an installation, which fuses leading edge digital technologies with bacterial bioart, biohacking, traditional media and altered artefacts, to artistically investigate the emerging technology of whole genome sequencing of bacteria and consider what it means to us personally, culturally and socially. This emerging technology is currently being developed and tested as a diagnostic and epidemiological tool within the UK health service.

          The project involves collaborations with micro-biologists, bioinformaticians, computer scientists and ethicists from the Modernising Medical Microbiology Project (a collaboration between Public Health England and the University of Oxford), the University of Hertfordshire, and the Wellcome Trust Brighton and Sussex Centre for Global Health Research.

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          Prediction of Staphylococcus aureus Antimicrobial Resistance by Whole-Genome Sequencing

          Whole-genome sequencing (WGS) could potentially provide a single platform for extracting all the information required to predict an organism's phenotype. However, its ability to provide accurate predictions has not yet been demonstrated in large independent studies of specific organisms. In this study, we aimed to develop a genotypic prediction method for antimicrobial susceptibilities. The whole genomes of 501 unrelated Staphylococcus aureus isolates were sequenced, and the assembled genomes were interrogated using BLASTn for a panel of known resistance determinants (chromosomal mutations and genes carried on plasmids). Results were compared with phenotypic susceptibility testing for 12 commonly used antimicrobial agents (penicillin, methicillin, erythromycin, clindamycin, tetracycline, ciprofloxacin, vancomycin, trimethoprim, gentamicin, fusidic acid, rifampin, and mupirocin) performed by the routine clinical laboratory. We investigated discrepancies by repeat susceptibility testing and manual inspection of the sequences and used this information to optimize the resistance determinant panel and BLASTn algorithm. We then tested performance of the optimized tool in an independent validation set of 491 unrelated isolates, with phenotypic results obtained in duplicate by automated broth dilution (BD Phoenix) and disc diffusion. In the validation set, the overall sensitivity and specificity of the genomic prediction method were 0.97 (95% confidence interval [95% CI], 0.95 to 0.98) and 0.99 (95% CI, 0.99 to 1), respectively, compared to standard susceptibility testing methods. The very major error rate was 0.5%, and the major error rate was 0.7%. WGS was as sensitive and specific as routine antimicrobial susceptibility testing methods. WGS is a promising alternative to culture methods for resistance prediction in S. aureus and ultimately other major bacterial pathogens.
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            Author and article information

            Contributors
            Conference
            July 2015
            July 2015
            : 367-368
            Affiliations
            Modernising Medical Microbiology Project

            (University of Oxford)

            University of Hertfordshire

            The Wellcome Trust Brighton and Sussex

            Centre for Global Health Research

            (Brighton and Sussex Medical School)

            20 Victory Mews, Brighton BN2 5XA, UK
            20 Victory Mews, Brighton BN2 5XA, UK
            Article
            10.14236/ewic/eva2015.80
            © Anna Dumitriu et al. Published by BCS Learning and Development Ltd. Proceedings of EVA London 2015, UK

            This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

            Electronic Visualisation and the Arts (EVA 2015)
            EVA
            London, UK
            7 & 9 July 2015
            Electronic Workshops in Computing (eWiC)
            Electronic Visualisation and the Arts
            Product
            Product Information: 1477-9358BCS Learning & Development
            Self URI (journal page): https://ewic.bcs.org/
            Categories
            Electronic Workshops in Computing

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