Smart lattice light-sheet microscopy for imaging rare and complex cellular events.

Light-sheet microscopes enable rapid high-resolution imaging of biological specimens; however, biological processes span spatiotemporal scales. Moreover, long-term phenotypes are often instigated by rare or fleeting biological events that are difficult to capture with a single imaging modality. Here, to overcome this limitation, we present smartLLSM, a microscope that incorporates artificial intelligence-based instrument control to autonomously switch between epifluorescent inverted imaging and lattice light-sheet microscopy (LLSM). We apply this approach to two unique processes: cell division and immune synapse formation. In each context, smartLLSM provides population-level statistics across thousands of cells and autonomously captures multicolor three-dimensional datasets or four-dimensional time-lapse movies of rare events at rates that dramatically exceed human capabilities. From this, we quantify the effects of Taxol dose on spindle structure and kinetochore dynamics in dividing cells and of antigen strength on cytotoxic T lymphocyte engagement and lytic granule polarization at the immune synapse. Overall, smartLLSM efficiently detects rare events within heterogeneous cell populations and records these processes with high spatiotemporal four-dimensional imaging over statistically significant replicates.

Smart Lattice Light Sheet Microscopy for imaging rare and complex cellular events.

Light sheet microscopes enable rapid, high-resolution imaging of biological specimens; however, biological processes span a variety of spatiotemporal scales. Moreover, long-term phenotypes are often instigated by rare or fleeting biological events that are difficult to capture with a single imaging modality and constant imaging parameters. To overcome this limitation, we present smartLLSM, a microscope that incorporates AI-based instrument control to autonomously switch between epifluorescent inverted imaging and lattice light sheet microscopy. We apply this technology to two major scenarios. First, we demonstrate that the instrument provides population-level statistics of cell cycle states across thousands of cells on a coverslip. Second, we show that by using real-time image feedback to switch between imaging modes, the instrument autonomously captures multicolor 3D datasets or 4D time-lapse movies of dividing cells at rates that dramatically exceed human capabilities. Quantitative image analysis on high-content + high-throughput datasets reveal kinetochore and chromosome dynamics in dividing cells and determine the effects of drug perturbation on cells in specific mitotic stages. This new methodology enables efficient detection of rare events within a heterogeneous cell population and records these processes with high spatiotemporal 4D imaging over statistically significant replicates.