Abstract: Systems and methods are provided for classifying microbial cells according to morphological features of microcolonies. A dark-field objective is employed to acquire a dark-field image of a microcolony during a microcolony growth phase that is characterized by phenotypic expression of microcolony morphological features which evolve with time and are differentiated among classes of microbial cell types. The dark-field image is processed to classify the microcolony according to two or more microbial cell types, such as Gram status and/or speciation. The dark-field objective may have a numerical aperture selected to facilitate the imaging of microcolony morphological features, residing, for example, between 0.15 and 0.35. A set of dark-field images of a microcolony may be collected during the microcolony growth phase and processed to classify the microcolony. Classification may be performed according to a temporal ordering of the dark-field images, for example, using a recurrent neural network.

Abstract: An integrated fluidic device is employed to perform microbial cell separation, in situ microcolony growth, and optional identification and antimicrobial susceptibility testing. While the integrated fluidic device is maintained in a closed state, microbial cell separation is performed to provide a microbial cell suspension that is contacted with a solid phase growth medium. A liquid component of the suspension is removed, thereby retaining microbial cells on the growth medium for incubation, growth, and subsequent harvesting and characterization. In some embodiments, antimicrobial susceptibility testing is performed by contacting growth media with a solid support having an antimicrobial agent provided thereon, such that the antimicrobial agent diffuses into a subregion of the growth medium that is accessible through an aperture surrounded, at least in part, by the solid support.