ABSTRACT Objectives Antibiotic resistant bacteria are an immense and rapidly growing medical problem affecting Veterans, combat warriors, and the broader population. Some infections are now considered “untreatable,” threatening to return us to the pre-antibiotic era. Heteroresistance (HR) is an under-recognized yet widespread form of antibiotic resistance in which a bacterial strain harbors a minor subpopulation of resistant cells co-existing with a majority susceptible population. We showed that even when as infrequent as 1 in 1 million, these resistant cells can rapidly replicate despite antibiotic treatment and thus cause treatment failure. However, we discovered a way to exploit HR as the basis of effective combination therapy; when two drugs to which an isolate exhibits HR are combined, each drug kills the cells resistant to the other and together they eradicate the infection. To avoid monotherapy failures and select effective combination regimens, it is important to identify HR during clinical antibiotic susceptibility testing (AST). However, current AST cannot detect and distinguish HR. This proposal will develop a novel AST platform to detect HR, potentially leading to improved patient outcomes. Research Plan Preliminary data suggest that optical interferometry can accurately and rapidly (1.5 hours) detect HR, as well as outperforming current diagnostics in differentiating standard resistance (in which 100% of cells are resistant) from susceptibility. We will elucidate optimal functional parameters for interferometry-based AST to balance sensitivity, accuracy, and speed. We will then test the efficacy of the interferometry AST on a broad panel of clinical bacterial isolates with diverse antibiotic resistance profiles, enhancing the system through an iterative process. We will extend the indications of the system, determining if it is effective on spiked blood cultures, abrogating the need for testing of pure colonies and further enhancing sample processing speed. Finally, we will retrospectively study a collection of bacteria from 2 clinical trials, testing the ability of interferometry to accurately detect HR as well as the association of HR with clinical outcomes. Methods This proposal is based on the innovative use of optical interferometry, a physics and material sciences technology, to detect antibiotic resistance including HR. Interferometry generates a topographic map of the surface of a bacterial population grown on agar with different respective antibiotics. “Peaks” of growing, resistant cells are easily distinguished from “valleys” of non-growing, susceptible cells. Clinical Relevance The research in this proposal has the potential to provide clinicians with the most accurate and comprehensive antibiotic resistance profile of bacterial strains. This could significantly improve the way antibiotics are selected for therapy, helping to avoid unnecessary failures, and identifying effective combination therapies to treat infections c...