@article {70293, title = {Machine learning-guided spatial omics for tissue-scale discovery of cell-type-specific architectures}, journal = {bioRxiv}, year = {2026}, month = {2026 Feb 13}, abstract = {

Multiplexed protein imaging enables spatially resolved analysis of molecular organization in tissues, but existing spatial proteomics platforms remain constrained in scalability, throughput, and integration with RNA measurements and interpretable computational analysis. Here, we present an integrated spatial omics framework that combines highly multiplexed protein and RNA imaging with explainable machine learning to map cell-type-specific molecular and structural architectures at tissue scale. Using this platform, we simultaneously profiled up to 46 proteins and 79 RNA species across \~370,000 cells in intact mouse brain tissue at diffraction-limited subcellular resolution (\~260 nm). We developed a scalable, open-source computational pipeline for large-scale image processing and analysis, and show that nuclear protein and chromatin features alone are sufficient to accurately classify brain cell types and their spatial organization. Incorporation of explainable deep learning further enabled identification of human-interpretable, cell-type-specific subnuclear structural features directly from imaging data, with independent quantitative validation. Together, this integrated experimental and computational framework enables tissue-scale spatial proteomics-based cell-type classification and structural feature discovery, providing a broadly applicable platform for mechanistic studies, high-content screening, and translational applications.

}, doi = {10.64898/2026.02.12.705598}, url = {https://www.biorxiv.org/content/early/2026/02/13/2026.02.12.705598}, author = {Lian, Yumin and Adjavon, Diane-Yayra and Kawase, Takashi and Kim, Jun and Fleishman, Greg and Preibisch, Stephan and Funke, Jan and Liu, Zhe J.} } @article {69457, title = {Deep-tissue transcriptomics and subcellular imaging at high spatial resolution}, journal = {Science}, year = {2025}, month = {2025 Feb 20}, abstract = {

Limited color channels in fluorescence microscopy have long constrained spatial analysis in biological specimens. Here, we introduce cycle Hybridization Chain Reaction (HCR), a method that integrates multicycle DNA barcoding with HCR to overcome this limitation. cycleHCR enables highly multiplexed imaging of RNA and proteins using a unified barcode system. Whole-embryo transcriptomics imaging achieved precise three-dimensional gene expression and cell fate mapping across a specimen depth of ~310 μm. When combined with expansion microscopy, cycleHCR revealed an intricate network of 10 subcellular structures in mouse embryonic fibroblasts. In mouse hippocampal slices, multiplex RNA and protein imaging uncovered complex gene expression gradients and cell-type-specific nuclear structural variations. cycleHCR provides a quantitative framework for elucidating spatial regulation in deep tissue contexts for research and potentially diagnostic applications.

bioRxiv preprint:\ 10.1101/2024.05.17.594641

}, doi = { 10.1126/science.adq2084}, url = {https://www.science.org/doi/10.1126/science.adq2084}, author = {Gandin, Valentina and Kim, Jun and Yang, Liang-Zhong and Lian, Yumin and Kawase, Takashi and Hu, Amy and Rokicki, Konrad and Fleishman, Greg and Tillberg, Paul and Aguilera Castrejon, Alejandro and Stringer, Carsen and Preibisch, Stephan and Liu, Zhe J.} } @article {69994, title = {A Multimodal Adaptive Optical Microscope For In Vivo Imaging from Molecules to Organisms}, journal = {bioRxiv}, year = {2025}, month = {2025 Jun 16}, abstract = {

Understanding biological systems requires observing features and processes across vast spatial and temporal scales, spanning nanometers to centimeters and milliseconds to days, often using multiple imaging modalities within complex native microenvironments. Yet, achieving this comprehensive view is challenging because microscopes optimized for specific tasks typically lack versatility due to inherent optical and sample handling trade-offs, and frequently suffer performance degradation from sample-induced optical aberrations in multicellular contexts. Here, we present MOSAIC, a reconfigurable microscope that integrates multiple advanced imaging techniques including light-sheet, label-free, super-resolution, and multi-photon, all equipped with adaptive optics. MOSAIC enables non-invasive imaging of subcellular dynamics in both cultured cells and live multicellular organisms, nanoscale mapping of molecular architectures across millimeter-scale expanded tissues, and structural/functional neural imaging within live mice. MOSAIC facilitates correlative studies across biological scales within the same specimen, providing an integrated platform for broad biological investigation.

Preprint:\ https://www.biorxiv.org/content/early/2025/06/13/2025.06.02.657494

}, doi = {10.1101/2025.06.02.657494}, url = {https://www.biorxiv.org/content/early/2025/06/13/2025.06.02.657494}, author = {Fu, Tian-Ming and Liu, Gaoxiang and Milkie, Daniel E. and Ruan, Xiongtao and G{\"o}rlitz, Frederik and Shi, Yu and Ferro, Valentina and Divekar, Nikita S. and Wang, Wei and York, Harrison M. and Kilic, Velat and Mueller, Matthew and Liang, Yajie and Daugird, Timothy A. and Gacha-Garay, Maria J. and Larkin, Kathryn A. and Adikes, Rebecca C. and Harrison, Nathaniel and Shirazinejad, Cyna and Williams, Samara and Nourse, Jamison L. and Sheu, Shu-Hsien and Gao, Liang and Li, Tongchao and Mondal, Chandrani and Achour, Kemal and Hercule, Wilmene and Stabley, Daniel and Emmerich, Kevin and Dong, Peng and Drubin, David and Liu, Zhe J. and Clapham, David and Mumm, Jeff S. and Koyama, Minoru and Killilea, Alison and Bravo-Cordero, Jose Javier and Keene, C. Dirk and Luo, Liqun and Kirchhausen, Tom and Pathak, Medha M. and Arumugam, Senthil and Nunez, James K. and Gao, Ruixuan and Matus, David Q. and Martin, Benjamin L. and Swinburne, Ian A. and Betzig, Eric and Legant, Wesley R. and Upadhyayula, Srigokul} } @article {69042, title = {Optimized Red-Absorbing Dyes for Imaging and Sensing}, journal = {Journal of the American Chemical Society}, year = {2023}, month = {2023 Oct 16}, abstract = {

Rhodamine dyes are excellent scaffolds for developing a broad range of fluorescent probes. A key property of rhodamines is their equilibrium between a colorless lactone and fluorescent zwitterion. Tuning the lactone{\textendash}zwitterion equilibrium constant (KL{\textendash}Z) can optimize dye properties for specific biological applications. Here, we use known and novel organic chemistry to prepare a comprehensive collection of rhodamine dyes to elucidate the structure{\textendash}activity relationships that govern\ KL{\textendash}Z. We discovered that the auxochrome substituent strongly affects the lactone{\textendash}zwitterion equilibrium, providing a roadmap for the rational design of improved rhodamine dyes. Electron-donating auxochromes, such as julolidine, work in tandem with fluorinated pendant phenyl rings to yield bright, red-shifted fluorophores for live-cell single-particle tracking (SPT) and multicolor imaging. The\ N-aryl auxochrome combined with fluorination yields red-shifted F{\"o}rster resonance energy transfer (FRET) quencher dyes useful for creating a new semisynthetic indicator to sense cAMP using fluorescence lifetime imaging microscopy (FLIM). Together, this work expands the synthetic methods available for rhodamine synthesis, generates new reagents for advanced fluorescence imaging experiments, and describes structure{\textendash}activity relationships that will guide the design of future probes.

}, issn = {0002-7863}, doi = {10.1021/jacs.3c0527310.1021/jacs.3c05273}, url = {https://pubs.acs.org/doi/10.1021/jacs.3c05273}, author = {Grimm, Jonathan B. and Tkachuk, Ariana N. and Patel, Ronak and Hennigan, S. Thomas and Gutu, Alina and Dong, Peng and Gandin, Valentina and Osowski, Anastasia M. and Holland, Katie L. and Liu, Zhe J. and Brown, Timothy A. and Lavis, Luke D.} }