Ultrack: pushing the limits of cell tracking across biological scales.

Tracking live cells across 2D, 3D, and multi-channel time-lapse recordings is crucial for understanding tissue-scale biological processes. Despite advancements in imaging technology, achieving accurate cell tracking remains challenging, particularly in complex and crowded tissues where cell segmentation is often ambiguous. We present Ultrack, a versatile and scalable cell-tracking method that tackles this challenge by considering candidate segmentations derived from multiple algorithms and parameter sets. Ultrack employs temporal consistency to select optimal segments, ensuring robust performance even under segmentation uncertainty. We validate our method on diverse datasets, including terabyte-scale developmental time-lapses of zebrafish, fruit fly, and nematode embryos, as well as multi-color and label-free cellular imaging. We show that Ultrack achieves state-of-the-art performance on the Cell Tracking Challenge and demonstrates superior accuracy in tracking densely packed embryonic cells over extended periods. Moreover, we propose an approach to tracking validation via dual-channel sparse labeling that enables high-fidelity ground truth generation, pushing the boundaries of long-term cell tracking assessment. Our method is freely available as a Python package with Fiji and napari plugins and can be deployed in a high-performance computing environment, facilitating widespread adoption by the research community.

Mantis: High-throughput 4D imaging and analysis of the molecular and physical architecture of cells.

High-throughput dynamic imaging of cells and organelles is essential for understanding complex cellular responses. We report Mantis, a high-throughput 4D microscope that integrates two complementary, gentle, live-cell imaging technologies: remote-refocus label-free microscopy and oblique light-sheet fluorescence microscopy. Additionally, we report shrimPy (Smart High-throughput Robust Imaging and Measurement in Python), an open-source software for high-throughput imaging, deconvolution, and single-cell phenotyping of 4D data. Using Mantis and shrimPy, we achieved high-content correlative imaging of molecular dynamics and the physical architecture of 20 cell lines every 15 min over 7.5 h. This platform also facilitated detailed measurements of the impacts of viral infection on the architecture of host cells and host proteins. The Mantis platform can enable high-throughput profiling of intracellular dynamics, long-term imaging and analysis of cellular responses to perturbations, and live-cell optical screens to dissect gene regulatory networks.

Mantis: high-throughput 4D imaging and analysis of the molecular and physical architecture of cells.

High-throughput dynamic imaging of cells and organelles is essential for understanding complex cellular responses. We report Mantis, a high-throughput 4D microscope that integrates two complementary, gentle, live-cell imaging technologies: remote-refocus label-free microscopy and oblique light-sheet fluorescence microscopy. Additionally, we report shrimPy, an open-source software for high-throughput imaging, deconvolution, and single-cell phenotyping of 4D data. Using Mantis and shrimPy, we achieved high-content correlative imaging of molecular dynamics and the physical architecture of 20 cell lines every 15 minutes over 7.5 hours. This platform also facilitated detailed measurements of the impacts of viral infection on the architecture of host cells and host proteins. The Mantis platform can enable high-throughput profiling of intracellular dynamics, long-term imaging and analysis of cellular responses to perturbations, and live-cell optical screens to dissect gene regulatory networks.