Abstract
This talk presents our team’s technological advances, application breakthroughs, and platform development over the past decade in live-cell super-resolution imaging, cross-scale functional imaging, and image reconstruction. It begins with a retrospective overview of a series of original methods developed by the team, including Hessian-SIM, SR-FACT, 4Pi-SIM, 3D-MP-SIM, and Sparse deconvolution. These advances highlight how reducing phototoxicity, improving spatiotemporal resolution, expanding the field of view, and strengthening quantitative reconstruction have collectively driven live-cell and in vivo imaging from merely “seeing” to “seeing accurately, comprehensively, and rapidly.”
In applying these imaging tools to investigate disease mechanisms, the talk highlights three representative achievements. First, live-cell super-resolution imaging revealed that the subcellular mislocalization of mutant proteins is directly associated with clinical severity in rare diseases such as hypomyelinating leukodystrophy, suggesting that abnormal protein localization may be a key determinant of disease phenotype and providing a basis for drug repurposing screens. Second, by integrating super-resolved mitochondrial morphology with single-cell transcriptomic analysis, we established a more biologically meaningful classification and transition trajectory of hematopoietic stem cells from youth to aging, identified key regulatory factors such as GDF15, and functionally validated their roles in controlling the fate of aged hematopoietic stem cells. Third, through multilevel cross-scale imaging spanning vesicles, cells, and pancreatic islets, we proposed a new model in which both synchronized and asynchronous secretion from a small subset of “readily releasable” β cells jointly determine biphasic insulin secretion in response to glucose stimulation, thereby revealing the importance of tissue-level emergent mechanisms in diabetes research.
Finally, the talk further elaborates our vision for the National Biomedical Imaging Center and the Virtualized, Verifiable, Integrated Twin Architecture for Life (VITAL) initiative: centered on the integration of macro-, meso-, and micro-scale imaging, multimodal fusion, and AI-enabled analysis, these efforts aim to enable holistic interrogation of complex living systems and to unify digital representation, closed-loop experimental validation, and cross-scale integration within a single framework.
About the Speaker
Liangyi Chen is a Boya Distinguished Professor at Peking University, a New Cornerstone Investigator, and Director of the National Biomedical Imaging Center. He develops quantitative measurements that make inaccessible processes in living cells and animals observable and distinguish competing biological mechanisms.