TY - JOUR
AU1 - Hughes, Diarmaid
AU2 - Andersson, Dan I.
AB - The ability to predict the evolutionary trajectories of antibiotic resistance would be of great value in tailoring dosing regimens of antibiotics so as to maximize the duration of their usefulness. Useful prediction of resistance evolution requires information about (a) the mutation supply rate, (b) the level of resistance conferred by the resistance mechanism, (c) the fitness of the antibiotic-resistant mutant bacteria as a function of drug concentration, and (d) the strength of selective pressures. In addition, processes including epistatic interactions and compensatory evolution, coselection of drug resistances, and population bottlenecks and clonal interference can strongly influence resistance evolution and thereby complicate attempts at prediction. Currently, the very limited quantitative data on most of these parameters severely limit attempts to accurately predict trajectories of resistance evolution.
TI - Evolutionary Trajectories to Antibiotic Resistance
JF - Annual Review of Microbiology
DO - 10.1146/annurev-micro-090816-093813
DA - 2017-09-08
UR - https://www.deepdyve.com/lp/annual-reviews/evolutionary-trajectories-to-antibiotic-resistance-MggRBp0bSF
SP - 579
EP - 596
VL - 71
IS - 
DP - DeepDyve
ER -