@article {69142, title = {Image processing tools for petabyte-scale light sheet microscopy data.}, journal = {Nat. Methods}, year = {2024}, month = {2024 Oct 17}, abstract = {

Light sheet microscopy is a powerful technique for high-speed three-dimensional imaging of subcellular dynamics and large biological specimens. However, it often generates datasets ranging from hundreds of gigabytes to petabytes in size for a single experiment. Conventional computational tools process such images far slower than the time to acquire them and often fail outright due to memory limitations. To address these challenges, we present PetaKit5D, a scalable software solution for efficient petabyte-scale light sheet image processing. This software incorporates a suite of commonly used processing tools that are optimized for memory and performance. Notable advancements include rapid image readers and writers, fast and memory-efficient geometric transformations, high-performance Richardson-Lucy deconvolution and scalable Zarr-based stitching. These features outperform state-of-the-art methods by over one order of magnitude, enabling the processing of petabyte-scale image data at the full teravoxel rates of modern imaging cameras. The software opens new avenues for biological discoveries through large-scale imaging experiments.

}, doi = {10.1038/s41592-024-02475-4}, url = {https://doi.org/10.1038/s41592-024-02475-4}, author = {Xiongtao Ruan and Matthew Mueller and Gaoxiang Liu and Frederik G{\"o}rlitz and Tian-Ming Fu and Daniel E. Milkie and Joshua Lillvis and Alison Killilea and Eric Betzig and Srigokul Upadhyayula} } @article {68655, title = {Smart Lattice Light Sheet Microscopy for imaging rare and complex cellular events}, journal = {Nature Methods}, volume = {21}, year = {2024}, month = {2024 Feb 01}, pages = {301-310}, abstract = {

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.

}, doi = {10.1038/s41592-023-02126-0}, url = {https://doi.org/10.1038/s41592-023-02126-0}, author = {Yu Shi and Jimmy S. Tabet and Daniel E. Milkie and Timothy A. Daugird and Chelsea Q. Yang and Andrea Giovannucci and Wesley R. Legant} } @article {68257, title = {Characterization, Comparison, and Optimization of Lattice Light Sheets}, journal = {Science Advances}, year = {2023}, month = {2023 Mar 31}, abstract = {

Lattice light sheet microscopy excels at the non-invasive imaging of three-dimensional (3D) dynamic processes at high spatiotemporal resolution within cells and developing embryos. Recently, several papers have called into question the performance of lattice light sheets relative to the Gaussian sheets most common in light sheet microscopy. Here we undertake a comprehensive theoretical and experimental analysis of various forms of light sheet microscopy which both demonstrates and explains why lattice light sheets provide significant improvements in resolution and photobleaching reduction. The analysis provides a procedure to select the correct light sheet for a desired experiment and specifies the processing that maximizes the use of all fluorescence generated within the light sheet excitation envelope for optimal resolution while minimizing image artifacts and photodamage. Development of a new type of {\textquotedblleft}harmonic balanced{\textquotedblright} lattice light sheet is shown to improve performance at all spatial frequencies within its 3D resolution limits and maintains this performance over lengthened propagation distances allowing for expanded fields of view.

}, doi = {10.1126/sciadv.ade6623}, url = {https://doi.org/10.1126/sciadv.ade6623}, author = {Gaoxiang Liu and Xiongtao Ruan and Daniel E. Milkie and Frederik G{\"o}rlitz and Matthew Mueller and Wilmene Hercule and Alison Kililea and Eric Betzig and Srigokul Upadhyayula} } @article {67849, title = {Rapid reconstruction of neural circuits using tissue expansion and lattice light sheet microscopy}, journal = {eLife}, year = {2022}, month = {2022 Oct 26}, abstract = {

Electron microscopy (EM) allows for the reconstruction of dense neuronal connectomes but suffers from low throughput, limiting its application to small numbers of reference specimens. We developed a protocol and analysis pipeline using tissue expansion and lattice light-sheet microscopy (ExLLSM) to rapidly reconstruct selected circuits across many samples with single synapse resolution and molecular contrast. We validate this approach in\ Drosophila, demonstrating that it yields synaptic counts similar to those obtained by EM, can be used to compare counts across sex and experience, and to correlate structural connectivity with functional connectivity. This approach fills a critical methodological gap in studying variability in the structure and function of neural circuits across individuals within and between species.

}, doi = {10.7554/eLife.81248}, url = {https://doi.org/10.7554/eLife.81248}, author = {Joshua L. Lillvis and Hideo Otsuna and Xiaoyu Ding and Igor Pisarev and Takashi Kawase and Jennifer Colonell and Konrad Rokicki and Cristian Goina and Ruixuan Gao and Amy Hu and Kaiyu Wang and John Bogovic and Daniel E. Milkie and Edward S. Boyden and Stephan Saalfeld and Paul W. Tillberg and Barry J. Dickson} } @article {65895, title = {An adaptive optics module for deep tissue multiphoton imaging in vivo}, journal = {Nature Methods}, year = {2021}, month = {2021 Oct 04}, pages = {1259-64}, abstract = {

Understanding complex biological systems requires visualizing structures and processes deep within living organisms. We developed a compact adaptive optics module and incorporated it into two- and three-photon fluorescence microscopes, to measure and correct tissue-induced aberrations. We resolved synaptic structures in deep cortical and subcortical areas of the mouse brain, and demonstrated high-resolution imaging of neuronal structures and somatosensory-evoked calcium responses in the mouse spinal cord at unprecedented depths\ in vivo.

}, doi = {10.1038/s41592-021-01279-0}, author = {Cristina Rodr{\'\i}guez and Anderson Chen and Jos{\'e} A. Rivera and Manuel A. Mohr and Yajie liang and Wenzhi Sun and Daniel E. Milkie and Thomas G. Bifano and Xiaoke Chen and Na Ji} }