we utilize single-molecule microscopy to localize and track fluorescently labeled chaperone and effector proteins in live Yersinia enterocolitica cells, a human pathogen in which the three phases of secretion can be physically and chemically controlled. By combining single-molecule tracking with bacterial genetics, we determine the prevalent diffusive states of chaperone proteins and chaperone:effector protein complexes in the presence and absence of their (putative) cytosolic binding partners. The results allow us to test whether the temporal hierarchy of secretion is regulated by cytosolic T3SS components that interact with chaperone:effector substrates either at the injectisome or while diffusing freely in the cytosol. Understanding the mechanism of temporally-ordered secretion may reveal new strategies for targeted anti-virulence therapies and enable the controlled use of T3SSs for therapeutic purposes.

50,000 deaths each year. Despite major advances in treatment (i.e., surgery, radiation therapy, chemotherapy, biologic/immune therapy) and resultant improved outcomes over time, it has been demonstrated that failure of treatment in patients with metastatic breast cancer portends a poor prognosis. As the number of potential FDA-approved cancer drugs increases, the likelihood of identifying effective combination strategies tailored to an individual patient's tumor increases. Therefore, to provide significant advances in cancer treatment and enable the most effective chemotherapy, development of more quantitative and objective means for assessing drug sensitivity of an individual patient's tumor that is safer, faster, sensitive and capable for single-or multidrug testing is urgently needed for advancing personalized therapies. To develop such an approach, fluorescence spectroscopic technologies may serve as a non-invasive means of revealing cell health. We applied phasorfluorescence lifetime imaging microscopy (phasor-FLIM) to measure drug response using human colorectal cancer cell line HCT116 and patient samples. FLIM can be served as a promising new approach for reading the metabolic states of cancer cells treated with anti-cancer therapeutics and identified specific alterations of metabolic states that are early indicators of irreversible cell demise and that such metabolic changes can be detected using a labelfree imaging assay for single-cell drug testing of rare and/or heterogeneous cancer cells. Based on these findings, we apply the label-free imaging platform to measure drug response using patient samples.

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