3D localization of retrovirus assembly in the presence of structured background with deep learning

Human immunodeficiency virus type 1 (HIV-1) particle assembly is driven by the Gag structural polyprotein and is a crucial step in the production of new virus particles. Elucidating the details of this process is necessary to fully understand the virus replication cycle. Real-time measurements of virus particle biogenesis in living cells have proved challenging, and most of our knowledge of this process to date has come from total internal fluorescence microscopy of labeled Gag at the bottom plasma membrane (PM) of adherent cells. While the glass coverslip adjacent to the bottom PM renders this an artificial environment, fluorescence measurements at the more physiologically relevant top PM are challenging due to the three-dimensional (3D) profile at the top PM as well as the large, structured background fluorescence that arises due to cytoplasmic, unassembled Gag protein. Here, we describe an approach to 3D localization microscopy and analysis to address the challenges associated with imaging virus assembly at the top PM in live cells. Specifically, we have employed the double helix point spread function for 3D imaging with an extended depth of field combined with a deep learning pipeline to analyze images that contain heterogeneous structured backgrounds. We demonstrate the power of this approach by measuring virus assembly at the top PM of adherent cells in 3D fluorescence microscopy and observe intriguing differences in the assembly kinetics and HIV-1 Gag puncta mobility between the adherent bottom PM and the nonadherent top PM.