title: Search Engine for Antimicrobial Resistance: A Cloud Compatible Pipeline and Web Interface for Rapidly Detecting Antimicrobial Resistance Genes Directly from Sequence Data.
abstract: BACKGROUND
  Antimicrobial resistance remains a growing and significant concern in human and veterinary medicine. Current laboratory methods for the detection and surveillance of antimicrobial resistant bacteria are limited in their effectiveness and scope. With the rapidly developing field of whole genome sequencing beginning to be utilised in clinical practice, the ability to interrogate sequencing data quickly and easily for the presence of antimicrobial resistance genes will become increasingly important and useful for informing clinical decisions. Additionally, use of such tools will provide insight into the dynamics of antimicrobial resistance genes in metagenomic samples such as those used in environmental monitoring.
  
  
  RESULTS
  Here we present the Search Engine for Antimicrobial Resistance (SEAR), a pipeline and web interface for detection of horizontally acquired antimicrobial resistance genes in raw sequencing data. The pipeline provides gene information, abundance estimation and the reconstructed sequence of antimicrobial resistance genes; it also provides web links to additional information on each gene. The pipeline utilises clustering and read mapping to annotate full-length genes relative to a user-defined database. It also uses local alignment of annotated genes to a range of online databases to provide additional information. We demonstrate SEAR's application in the detection and abundance estimation of antimicrobial resistance genes in two novel environmental metagenomes, 32 human faecal microbiome datasets and 126 clinical isolates of Shigella sonnei.
  
  
  CONCLUSIONS
  We have developed a pipeline that contributes to the improved capacity for antimicrobial resistance detection afforded by next generation sequencing technologies, allowing for rapid detection of antimicrobial resistance genes directly from sequencing data. SEAR uses raw sequencing data via an intuitive interface so can be run rapidly without requiring advanced bioinformatic skills or resources. Finally, we show that SEAR is effective in detecting antimicrobial resistance genes in metagenomic and isolate sequencing data from both environmental metagenomes and sequencing data from clinical isolates.
authors.affiliation: Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.
authors.forename: Will
authors.initials: W
authors.lastname: Rowe
authors.affiliation: Wellcome Trust Sanger Institute, Cambridge, United Kingdom.
authors.forename: Kate S
authors.initials: KS
authors.lastname: Baker
authors.affiliation: Centre for Environment, Fisheries and Aquaculture Science, Weymouth, United Kingdom.
authors.forename: David
authors.initials: D
authors.lastname: Verner-Jeffreys
authors.affiliation: Centre for Environment, Fisheries and Aquaculture Science, Weymouth, United Kingdom.
authors.forename: Craig
authors.initials: C
authors.lastname: Baker-Austin
authors.affiliation: Environment, Health and Safety, GlaxoSmithKline, Ware, United Kingdom.
authors.forename: Jim J
authors.initials: JJ
authors.lastname: Ryan
authors.affiliation: Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.
authors.forename: Duncan
authors.initials: D
authors.lastname: Maskell
authors.affiliation: Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.
authors.forename: Gareth
authors.initials: G
authors.lastname: Pearce
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods; D030541:Databases, Genetic; D004352:Drug Resistance, Microbial; D004784:Environmental Monitoring / Q000379:methods; D005243:Feces; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D020407:Internet; D054892:Metagenome; D058977:Molecular Sequence Annotation; D011381:Programming Languages; D057386:Search Engine; D012764:Shigella sonnei / Q000235:genetics; D012984:Software