Autophagy is a process in which normal cellular components that accumulate during growth and differentiation are degraded via the lysosome; it is a survival mechanism that reallocates nutrients from unnecessary processes to more vital processes in the cell. Basal levels of autophagy are usually low but can be up-regulated by numerous stimuli including starvation, physiological stress, pharmacological agents and infections. In addition, suppression of autophagy has been associated with cancer, neurodegenerative disorders, infectious diseases and inflammation. During autophagy, cytoplasmic LC3 is processed and recruited to the autophagosomal membranes; therefore, cells undergoing autophagy can be identified by visualizing LC3 puncta using immunofluorescence microscopy. While manual microscopy allows visual identification of autophagy on a per-cell basis, an objective and statistically rigorous assessment is difficult to obtain. To overcome these problems, we used the FlowSight imaging cytometry platform collect imagery of large numbers of cells to assess autophagy in an objective, quantitative, and statistically robust manner. In this study, we demonstrate a method for determining the best image-based parameter for assess the LC3 puncta in starved and non-starved U2OS RFP-LC3 human osteosarcoma reporter cells.
- Copyright © 2013 by The American Association of Immunologists, Inc.