Antimicrobial Resistance Prediction in PATRIC and RAST View Full Text


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Article Info

DATE

2016-06-14

AUTHORS

James J. Davis, Sébastien Boisvert, Thomas Brettin, Ronald W. Kenyon, Chunhong Mao, Robert Olson, Ross Overbeek, John Santerre, Maulik Shukla, Alice R. Wattam, Rebecca Will, Fangfang Xia, Rick Stevens

ABSTRACT

The emergence and spread of antimicrobial resistance (AMR) mechanisms in bacterial pathogens, coupled with the dwindling number of effective antibiotics, has created a global health crisis. Being able to identify the genetic mechanisms of AMR and predict the resistance phenotypes of bacterial pathogens prior to culturing could inform clinical decision-making and improve reaction time. At PATRIC (http://patricbrc.org/), we have been collecting bacterial genomes with AMR metadata for several years. In order to advance phenotype prediction and the identification of genomic regions relating to AMR, we have updated the PATRIC FTP server to enable access to genomes that are binned by their AMR phenotypes, as well as metadata including minimum inhibitory concentrations. Using this infrastructure, we custom built AdaBoost (adaptive boosting) machine learning classifiers for identifying carbapenem resistance in Acinetobacter baumannii, methicillin resistance in Staphylococcus aureus, and beta-lactam and co-trimoxazole resistance in Streptococcus pneumoniae with accuracies ranging from 88-99%. We also did this for isoniazid, kanamycin, ofloxacin, rifampicin, and streptomycin resistance in Mycobacterium tuberculosis, achieving accuracies ranging from 71-88%. This set of classifiers has been used to provide an initial framework for species-specific AMR phenotype and genomic feature prediction in the RAST and PATRIC annotation services. More... »

PAGES

27930

References to SciGraph publications

  • 2013-10-09. Explaining AdaBoost in EMPIRICAL INFERENCE
  • 2007-12. An increasing threat in hospitals: multidrug-resistant Acinetobacter baumannii in NATURE REVIEWS MICROBIOLOGY
  • 2002-01. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning in NATURE MEDICINE
  • 2014-03-03. Kraken: ultrafast metagenomic sequence classification using exact alignments in GENOME BIOLOGY
  • 2015-01-19. Evolutionary history and global spread of the Mycobacterium tuberculosis Beijing lineage in NATURE GENETICS
  • 2001-10. Random Forests in MACHINE LEARNING
  • 2014-11-22. Characterizing the genetic basis of bacterial phenotypes using genome-wide association studies: a new direction for bacteriology in GENOME MEDICINE
  • 2014-11-20. SRST2: Rapid genomic surveillance for public health and hospital microbiology labs in GENOME MEDICINE
  • 1995-09. Support-vector networks in MACHINE LEARNING
  • 2015-12-21. Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis in NATURE COMMUNICATIONS
  • 2015-01-07. A new antibiotic kills pathogens without detectable resistance in NATURE
  • 2014-02-09. Dense genomic sampling identifies highways of pneumococcal recombination in NATURE GENETICS
  • 2015-02-10. RASTtk: A modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes in SCIENTIFIC REPORTS
  • 2013-05-05. Population genomics of post-vaccine changes in pneumococcal epidemiology in NATURE GENETICS
  • 2013-10-11. A robust prognostic signature for hormone-positive node-negative breast cancer in GENOME MEDICINE
  • 2015-05-06. Derivation of a bronchial genomic classifier for lung cancer in a prospective study of patients undergoing diagnostic bronchoscopy in BMC MEDICAL GENOMICS
  • 2015-05-07. Machine learning applications in genetics and genomics in NATURE REVIEWS GENETICS
  • 2009-12-15. BLAST+: architecture and applications in BMC BIOINFORMATICS
  • 2014-12-01. Molecular mechanisms of antibiotic resistance in NATURE REVIEWS MICROBIOLOGY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/srep27930

    DOI

    http://dx.doi.org/10.1038/srep27930

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1039514060

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/27297683


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