In genomic analyses of BE tissues from patients with or without later progression to HGD or EAC, we found significantly higher numbers of TP53 mutations in BE from patients with subsequent progression. These mutations were frequently detected before the onset of dysplasia or substantial changes in copy number.

Different species exposed to a common stress may adapt by mutations in shared pathways or in unique systems, depending on how past environments have molded their genomes. Understanding how diverse bacterial pathogens evolve in response to an antimicrobial treatment is a pressing example of this problem, where discovery of molecular parallelism could lead to clinically useful predictions. Evolution experiments with pathogens in environments containing antibiotics, combined with periodic whole-population genome sequencing, can be used to identify many contending routes to antimicrobial resistance. We separately propagated two clinically relevant Gram-negative pathogens, Pseudomonas aeruginosa and Acinetobacter baumannii, in increasing concentrations of tobramycin in two different environments each: planktonic and biofilm. Independently of the pathogen, the populations adapted to tobramycin selection by parallel evolution of mutations in fusA1, encoding elongation factor G, and ptsP, encoding phosphoenolpyruvate phosphotransferase. As neither gene is a direct target of this aminoglycoside, mutations to either are unexpected and underreported causes of resistance. Additionally, both species acquired antibiotic resistance-associated mutations that were more prevalent in the biofilm lifestyle than in the planktonic lifestyle; these mutations were in electron transport chain components in A. baumannii and lipopolysaccharide biosynthesis enzymes in P. aeruginosa populations. Using existing databases, we discovered site-specific parallelism of fusA1 mutations that extends across bacterial phyla and clinical isolates. This study suggests that strong selective pressures, such as antibiotic treatment, may result in high levels of predictability in molecular targets of evolution, despite differences between organisms’ genetic backgrounds and environments. IMPORTANCE The rise of antimicrobial resistance is a leading medical threat, motivating efforts to forecast both its evolutionary dynamics and its genetic causes. Aminoglycosides are a major class of antibiotics that disrupt translation, but resistance may occur by a number of mechanisms. Here, we show the repeated evolution of resistance to the aminoglycoside tobramycin in both P. aeruginosa and A. baumannii via mutations in fusA1, encoding elongation factor G, and ptsP, encoding the nitrogen-specific phosphotransferase system. Laboratory evolution and whole-population genome sequencing were used to identify these targets, but mutations at identical amino acid positions were also found in published genomes of diverse bacterial species and clinical isolates. We also identified other resistance mechanisms associated with growth in biofilms that likely interfere with drug binding or uptake. Characterizing the evolution of multiple species in the presence of antibiotics can identify new, repeatable causes of resistance that may be predicted and counteracted by alternative treatment.

words)13 An important problem in evolution is identifying the genetic basis of how different species adapt 14 to similar environments. Understanding how various bacterial pathogens evolve in response to 15 antimicrobial treatment is a pressing example of this problem, where discovery of molecular 16 parallelism could lead to clinically useful predictions. Evolution experiments with pathogens in 17 environments containing antibiotics combined with periodic whole population genome 18 sequencing can be used to characterize the evolutionary dynamics of the pathways to 19 antimicrobial resistance. We separately propagated two clinically relevant Gram-negative 20 pathogens, Pseudomonas aeruginosa and Acinetobacter baumannii, in increasing 21 concentrations of tobramycin in two different environments each: planktonic and biofilm. 22Independent of the pathogen, populations adapted to tobramycin selection by parallel evolution 23 of mutations in fusA1, encoding elongation factor G, and ptsP, encoding phosphoenolpyruvate 24 phosphotransferase. As neither gene is a direct target of this aminoglycoside, both are relatively 25 novel and underreported causes of resistance. Additionally, both species acquired antibiotic-26 associated mutations that were more prevalent in the biofilm lifestyle than planktonic, in electron 27 transport chain components in A. baumannii and LPS biosynthesis enzymes in P. aeruginosa 28 populations. Using existing databases, we discovered both fusA1 and ptsP mutations to be 29 prevalent in antibiotic resistant clinical isolates. Additionally, we report site-specific parallelism of 30 fusA1 mutations that extend across several bacterial phyla. This study suggests that strong 31 selective pressures such as antibiotic treatment may result in high levels of predictability in 32 molecular targets of evolution despite differences between organisms' genetic background and 33 environment.The notion that evolution can be forecasted at the level of phenotype, gene, or even 36 amino acid is no longer a fantasy in the post-genomic era (Lässig et al., 2017). If we 37 acknowledge that most forecasting efforts rely on history to anticipate the future, the explosive 38 growth of whole-genome sequencing (WGS) sets the stage to resolve evolutionary phenomena 39 in action and suggest the next selected path. Among the best examples, bacterial populations 40 exposed to strong selection like antibiotics and analyzed by WGS are likely to identify gene 41 regions that produce resistance (Ahmed et al., 2018a; Cooper, 2018; Feng et al., 2016; Palmer 42 and Kishony, 2013). Repeated instances of the same antibiotic selection may enrich the same 43 types of mutations and ultimately enable some measure of predictability (Ibacache-Quiroga et 44 al., 2018; Wong et al., 2012). For instance, we can be confident that exposure of many bacteria 45 to high doses of fluoroquinolones like ciprofloxacin may select for substitutions in residues 83 or 46 87 of the drug target, DNA gyrase A (Fàbrega et al., 2009; Wong and Kassen, 2011).47 Furt...

INTRODUCTION: A risk prediction test was previously validated to predict progression to high-grade dysplasia (HGD) and esophageal adenocarcinoma (EAC) in patients with Barrett's esophagus (BE). The aim of our study was to independently validate this test to predict the risk of progression to HGD/EAC in BE patients with nondysplastic (ND), indefinite for dysplasia and low-grade dysplasia (LGD). METHODS: A single-blinded, case-control study was conducted to stratify patients with BE as low, intermediate, or high risk for progression to HGD/EAC within 5 years using a previously described risk prediction test. Patients with BE who progressed to HGD/EAC after at least 1 year (n = 58) were matched to patients undergoing surveillance without progression (n = 210, median surveillance 7 years). Baseline biopsies with subspecialist diagnoses of ND, indefinite for dysplasia, or LGD were tested in a blinded manner, and the predictive performance of the test was assessed. RESULTS: This risk prediction test stratified patients with BE based on progression risk with the high-risk group at 4.7-fold increased risk for HGD/EAC compared with the low-risk group (95% confidence interval 2.5–8.8, P < 0.0001). Prevalence-adjusted positive predictive value at 5 years was 23%. The high-risk class and male sex provided predictive power that was independent of pathologic diagnosis, age, segment length, and hiatal hernia. Patients with ND BE who scored high risk progressed at a higher rate (26%) than patients with subspecialist-confirmed LGD (21.8%) at 5 years. DISCUSSION: A risk prediction test identifies patients with ND BE who are at high risk for progression to HGD/EAC and may benefit from early endoscopic therapy or increased surveillance.

Experimental evolution is a powerful technique to understand how populations evolve from selective pressures imparted by the surrounding environment. With the advancement of whole-population genomic sequencing, it is possible to identify and track multiple contending genotypes associated with adaptations to specific selective pressures. This approach has been used repeatedly with model species in vitro, but only rarely in vivo. Herein we report results of replicate experimentally evolved populations of Streptococcus pneumoniae propagated by repeated murine nasal colonization with the aim of identifying gene products under strong selection as well as the population genetic dynamics of infection cycles. Frameshift mutations in one gene, dltB, responsible for incorporation of d-alanine into teichoic acids on the bacterial surface, evolved repeatedly and swept to high frequency. Targeted deletions of dltB produced a fitness advantage during initial nasal colonization coupled with a corresponding fitness disadvantage in the lungs during pulmonary infection. The underlying mechanism behind the fitness trade-off between these two niches was found to be enhanced adherence to respiratory cells balanced by increased sensitivity to host-derived antimicrobial peptides, a finding recapitulated in the murine model. Additional mutations that are predicted to affect trace metal transport, central metabolism, and regulation of biofilm production and competence were also selected. These data indicate that experimental evolution can be applied to murine models of pathogenesis to gain insight into organism-specific tissue tropisms. IMPORTANCE Evolution is a powerful force that can be experimentally harnessed to gain insight into how populations evolve in response to selective pressures. Herein we tested the applicability of experimental evolutionary approaches to gain insight into how the major human pathogen Streptococcus pneumoniae responds to repeated colonization events using a murine model. These studies revealed the population dynamics of repeated colonization events and demonstrated that in vivo experimental evolution resulted in highly reproducible trajectories that reflect the environmental niche encountered during nasal colonization. Mutations impacting the surface charge of the bacteria were repeatedly selected during colonization and provided a fitness benefit in this niche that was counterbalanced by a corresponding fitness defect during lung infection. These data indicate that experimental evolution can be applied to models of pathogenesis to gain insight into organism-specific tissue tropisms.