E.V., N.Ph., and C.K. this method should enable parallel screening of more antibiotics than is currently possible with available automated systems. This technology has the potential to revolutionize clinical practice by providing quick and accurate phenotypic AST data for virtually all available antibiotics in a single test. Introduction Timely administration of targeted antibiotics, determined by phenotypic antimicrobial susceptibility screening (AST), is essential not only for infectious disease patient care, but also for combatting the spread of antibiotic resistance1C4. Implementing the most appropriate clinical care requires quick and accurate diagnostic information5. Phenotypic AST assessments the ability of antibiotics to inhibit bacterial growth, thereby providing important actionable information to physicians to determine proper antibiotic therapies6. This test is most commonly accomplished by a variance of a broth microdilution assay (BMD), a method that determines minimum inhibitory concentrations (MICs) for each tested antibiotic for any bacterial isolate derived from a patient sample7. To determine an accurate MIC for a given antibiotic, a range of concentrations must be tested. Thus, AST panels comprise multiple antibiotics, each tested at multiple concentrations6. Phenotypic AST requires determining the difference between bacterial growth and the lack thereof, thereby limiting the velocity with which results can be obtained. The Clinical and Laboratory Alvimopan dihydrate Requirements Institute (CLSI) BMD reference method, Alvimopan dihydrate the gold standard phenotypic AST method, requires an incubation of 16C24 hours7. After this incubation period, results can be go through visually. Some automated AST platforms enable faster reporting by using sensitive optical readers or including metabolic probes during incubation to visualize bacteria earlier6,8. These systems periodically monitor (every 15C30?moments) every well of each panel and can statement FCRL5 results for some strains in as few as 4C8?hours. However, in practice, the platforms have reporting modes of 9C13?hours, and common times-to-result of 7C16?hours, rendering them overnight assays in many clinical laboratory workflows6,8,9. Furthermore, the presence of metabolic probes may compromise measurement accuracies by interfering with antibiotic-bacterium interactions10. Finally, because these assessments require periodic monitoring of every well on a test panel, introducing a new antibiotic necessitates removal of a different antibiotic or reduces the throughput of the overall system. The key to performing same-shift ( 6-hour) AST lies in developing an accurate and sensitive bacterial amplification method that does not affect cell growth and is able to account for shape-modifying growth modes that can be induced by antibiotics8. In addition to killing the organisms or preventing their replication, antibiotics can Alvimopan dihydrate cause significant changes in bacterial cell morphology prior to cell death. For example, upon binding to penicillin binding proteins (PBPs), beta-lactam antibiotics can induce temporary bacterial elongation (filamentation) Alvimopan dihydrate or swelling (protoplast or spheroplast) at antibiotic concentrations above MICs11. In these growth modes, bacteria enlarge but do not septate12,13. As a result, current automated systems, which measure bacterial density or metabolic activity, cannot accurately differentiate when bacterial cells are expanding in size versus dividing, and therefore cannot statement results in 6 hours6. Beta-lactams as a class account for 70% of US antibiotics prescriptions; thus, it is imperative Alvimopan dihydrate for a useful AST method to accurately capture their activity13. To elucidate bacterial morphologies, academic and industrial experts have recently developed multiple novel methods that enable individual bacteria to be interrogated8. These include high-power optical microscopy14, micromachined cantilevers15, microfluidic methods16, and circulation cytometry17. Although powerful technologies, the complexities of these platforms limit throughputs, increase per-test costs, and decrease the quantity of antibiotics that can be tested in.