23Surveillance of drug-resistant bacteria is essential for healthcare providers to deliver effective 24 empiric antibiotic therapy. However, traditional molecular epidemiology does not typically occur 25 on a timescale that could impact patient treatment and outcomes. Here we present a method 26 called 'genomic neighbor typing' for inferring the phenotype of a bacterial sample by identifying 27 its closest relatives in a database of genomes with metadata. We show that this technique can 28 infer antibiotic susceptibility and resistance for both S. pneumoniae and N. gonorrhoeae. We 29 implemented this with rapid k-mer matching, which, when used on Oxford Nanopore MinION 30 data, can run in real time. This resulted in determination of resistance within ten minutes 31 (sens/spec 91%/100% for S. pneumoniae and 81%/100% N. gonorrhoeae from isolates with a 32 representative database) of sequencing starting, and for clinical metagenomic sputum samples 33 (75%/100% for S. pneumoniae), within four hours of sample collection. This flexible approach has 34 wide application to pathogen surveillance and may be used to greatly accelerate appropriate 35 empirical antibiotic treatment. 36 45The molecular epidemiology of infectious disease allows us to identify high-risk pathogens and 46 determine their patterns of spread, on the basis of their genetics or (increasingly) genomics. 47Conventionally such studies, including outbreak investigations and characterization of novel 48 resistant strains, have been conducted in retrospect, but this has been changing with the 49 availability of new and increasingly inexpensive sequencing technologies 2,3 . The wealth of data 50 generated by genomics is promising but introduces a new challenge: while many features of a 51 sequence are correlated with the phenotype of interest, few are causative. 52 53 Prescription, however, has long been informed by correlative features when causative ones are 54 difficult to measure, for example whether the same syndrome or pathogen occurring in other 55 patients from the same clinical environment have responded to a particular antibiotic. This has 56 also been observed at the genetic level as well, as a result of genetic linkage between resistance 57 elements and the rest of the genome. An example is given by the pneumococcus (Streptococcus 58 pneumoniae). The Centers for Disease Control have rated the threat level of drug-resistant 59 pneumococcus as 'serious' 4 . While resistance arises in pneumococci through a variety of 60 mechanisms, approximately 90% of the variance in the minimal inhibitory concentration (MIC) 61 for antibiotics of different classes can be explained by the loci determining the strain type 5 , even 62 though none of these loci themselves causes resistance. Thus, in the overwhelming majority of 63 cases, resistance and susceptibility can be inferred from coarse strain typing based on population Results 81 82 Resistance is associated with clones in S. pneumoniae and N. gonorrhoeae 83 84 To quantify the association of clones with antibi...

21Quantitative assessment of antibiotic-responsive RNA transcripts holds promise for a 22 pump alleles acquired from commensal Neisseria, three resistant isolates with the C2611T 23s 126 rRNA mutation, and one resistant isolate with the A2059G 23s rRNA mutation (17, 18). A total 127 of ~258 million 50 bp paired-end reads were generated across 90 libraries. Each library had on 128 average 3.17 ± 0.16 million reads, and an average of 1.82 ± 0.11 million reads per library 129 mapped to the FA1090 (AE004969.1) reference genome. 130 131 Genetic distance and population structure impact transcriptome regulation 132

Neisseria commensals are an indisputable source of resistance for their pathogenic relatives; however, the evolutionary paths commensal species take to reduced susceptibility in this genus have been relatively underexplored. Here, we leverage in vitro selection as a powerful screen to identify the genetic adaptations that produce azithromycin resistance (≤ 2 μg/mL) in the Neisseria commensal, N. elongata. Across multiple lineages (n=7/16), we find mutations encoding resistance converge on the gene encoding the 50S ribosomal L34 protein (rpmH) and the intergenic region proximal to the 30S ribosomal S3 protein (rpsC) through duplication events. Importantly, one of the laboratory evolved mutations in rpmH is identical, and two nearly identical, to those recently reported to confer high-level resistance to azithromycin in N. gonorrhoeae. Transformations into the ancestral N. elongata lineage confirmed the causality of both rpmH and rpsC mutations. Though most lineages inheriting duplications suffered in vitro fitness costs, one variant showed no growth defect, suggesting the possibility that it may be sustained in natural populations. Finally, we assessed the potential of horizontal transfer of derived resistance mutations into multiple strains of N. gonorrhoeae. Though we were unable to transform N. gonorrhoeae in this case, studies like this will be critical for predicting commensal alleles that are at risk of rapid dissemination into pathogen populations.