RT Journal Article SR Electronic T1 Rapid heuristic inference of antibiotic resistance and susceptibility by genomic neighbor typing JF bioRxiv FD Cold Spring Harbor Laboratory SP 403204 DO 10.1101/403204 A1 Karel Břinda A1 Alanna Callendrello A1 Kevin C. Ma A1 Derek R MacFadden A1 Themoula Charalampous A1 Robyn S Lee A1 Lauren Cowley A1 Crista B Wadsworth A1 Yonatan H Grad A1 Gregory Kucherov A1 Justin O’Grady A1 Michael Baym A1 William P Hanage YR 2019 UL http://biorxiv.org/content/early/2019/08/07/403204.abstract AB Surveillance of drug-resistant bacteria is essential for healthcare providers to deliver effective empiric antibiotic therapy. However, traditional molecular epidemiology does not typically occur on a timescale that could impact patient treatment and outcomes. Here we present a method called ‘genomic neighbor typing’ for inferring the phenotype of a bacterial sample by identifying its closest relatives in a database of genomes with metadata. We show that this technique can infer antibiotic susceptibility and resistance for both S. pneumoniae and N. gonorrhoeae. We implemented this with rapid k-mer matching, which, when used on Oxford Nanopore MinION data, can run in real time. This resulted in determination of resistance within ten minutes (sens/spec 91%/100% for S. pneumoniae and 81%/100% N. gonorrhoeae from isolates with a representative database) of sequencing starting, and for clinical metagenomic sputum samples (75%/100% for S. pneumoniae), within four hours of sample collection. This flexible approach has wide application to pathogen surveillance and may be used to greatly accelerate appropriate empirical antibiotic treatment.