Huangqingbo Sun

All Publications

• Big1 is a cell-cycle regulator linking cell size to basal body number in Tetrahymena thermophila CURRENT BIOLOGY Stemm-Wolf, A. J., Soh, A., Mitchell, L. E., Sun, H., Collet, E., Dholakia, G. L., Raju, V., Hesselberth, J. R., Taliaferro, J., Murphy, R. F., Heasley, L. R., Pearson, C. G. 2026; 36 (7): 1882-1891

  Abstract

  Cell-size control is necessary for the optimum function and fitness of cells. In many eukaryotes, cell size is controlled through the initiation of cell division once a size threshold is achieved.1 Cells sense their size through the relationship of cell-size-dependent and independent factors, though the mechanistic details are known for few eukaryotes.2,3 An additional dimension of cell-size control is the subcellular localization and control of cell-cycle regulators. The cell cortex is a known site of cell-cycle regulator accumulation that maintains an established cell size based on surface area.4,5,6 Once cells commit to division, cyclins and their associated cyclin-dependent kinases (CDKs) coordinate DNA synthesis, mitosis, and cell division.7,8 Cyclin/CDK activity is regulated by multiple mechanisms,9,10,11,12,13,14 including by non-coding RNAs15 and RNA-binding proteins.16,17 Centrosomes are also activation sites of cyclin/CDKs and other cell-cycle regulators.18,19,20,21,22,23,24,25,26,27,28,29,30 The cortex of the ciliate Tetrahymena thermophila is distinguished by ciliary rows comprised of basal bodies (BBs), which are similar to the centrioles within centrosomes and the site of Tetrahymena CDK localization.31,32,33 The number of BBs per Tetrahymena cell remains consistent for each cell-cycle stage, even as the number and lengths of ciliary rows vary,34 indicating that the BB number is more regulated than cell volume. Utilizing the large-cell Tetrahymena big1-1 mutant strain,35 we identify Big1 to be an RNA-binding domain (RBD)-containing protein that localizes to BBs and controls cell size through its influence on cell-cycle progression, suggesting that BBs are a size-dependent measure of cell growth.

  View details for DOI 10.1016/j.cub.2026.02.065

  View details for Web of Science ID 001740714100001

  View details for PubMedID 41875877

  View details for PubMedCentralID PMC13014017

• Generative machine learning unlocks the first proteome-wide image of human cells. bioRxiv : the preprint server for biology Sun, H., Kahnert, K., Hansen, J. N., Leineweber, W., Li, M., Feng, W., Ballllosera, F., Axelsson, U., Ouyang, W., Lundberg, E. 2026

  Abstract

  The spatial organization of proteins within cells governs virtually all cellular functions. Yet, current imaging technologies can simultaneously visualize only tens of proteins, orders of magnitude below the thousands that populate a single human cell. Here, we present ProtiCelli, a deep generative model that simulates microscopy images for 12,800 human proteins from just three cellular landmark stains. Trained on 1.23 million images from the Human Protein Atlas, ProtiCelli outperforms existing methods in reconstruction accuracy and textural fidelity, and generalizes to unseen cell types and drug perturbations absent from training. We demonstrate that ProtiCelli-generated images preserve hierarchical subcellular organization, recapitulate known protein-protein interaction landscapes, and resolve compartment-specific functions of moonlighting proteins at the single-cell level. Remarkably, the model infers drug-induced changes in protein expression and localization from cell morphology alone, predicts cell cycle stage without dedicated cell cycle markers, and enables unsupervised segmentation of subcellular compartments as well as spatial decomposition of gene sets into functional regions. Ultimately, we leverage ProtiCelli to generate Proteome2Cell, an unprecedented dataset of 30.7 million simulated images creating 2,400 "virtual cells" across 12 human cell lines. These proteome-scale images enable the construction of hierarchical single-cell models that distinguish conserved from dynamic protein architectures. Integration of Pro- teome2Cell into the Human Protein Atlas democratizes the exploration of these "virtual cells". By computationally bridging the experimental scalability gap, ProtiCelli establishes a foundation for spatial virtual cell modeling and paves an avenue for transforming spatial proteomics from cataloging proteins to simulating complete cellular systems.

  View details for DOI 10.64898/2026.03.31.715748

  View details for PubMedID 41959450

  View details for PubMedCentralID PMC13060211

• Intrinsic heterogeneity of primary cilia revealed through spatial proteomics. Cell Hansen, J. N., Sun, H., Kahnert, K., Westenius, E., Johannesson, A., Villegas, C., Le, T., Tzavlaki, K., Winsnes, C., Pohjanen, E., Mäkiniemi, A., Fall, J., Ballllosera Navarro, F., Bäckström, A., Lindskog, C., Johansson, F., von Feilitzen, K., Delgado-Vega, A. M., Martinez Casals, A., Mahdessian, D., Uhlén, M., Sheu, S. H., Lindstrand, A., Axelsson, U., Lundberg, E. 2025

  Abstract

  Primary cilia are critical organelles found on most human cells. Their dysfunction is linked to hereditary ciliopathies with a wide phenotypic spectrum. Despite their significance, the specific roles of cilia in different cell types remain poorly understood due to limitations in analyzing ciliary protein composition. We employed antibody-based spatial proteomics to expand the Human Protein Atlas to primary cilia. Our analysis identified the subciliary locations of 715 proteins across three cell lines, examining 128,156 individual cilia. We found that 69% of the ciliary proteome is cell-type specific, and 78% exhibited single-cilia heterogeneity. Our findings portray cilia as sensors tuning their proteome to effectively sense the environment and compute cellular responses. We reveal 91 cilia proteins and found a genetic candidate variant in CREB3 in one clinical case with features overlapping ciliopathy phenotypes. This open, spatial cilia atlas advances research on cilia and ciliopathies.

  View details for DOI 10.1016/j.cell.2025.08.039

  View details for PubMedID 41005307

• Flexible and robust cell-type annotation for highly multiplexed tissue images. Cell systems Sun, H., Yu, S., Casals, A. M., Bäckström, A., Lu, Y., Lindskog, C., Ruffalo, M., Lundberg, E., Murphy, R. F. 2025: 101374

  Abstract

  Identifying cell types in highly multiplexed images is essential for understanding tissue spatial organization. Current cell-type annotation methods often rely on extensive reference images and manual adjustments. In this work, we present a tool, the Robust Image-Based Cell Annotator (RIBCA), that enables accurate, automated, unbiased, and fine-grained cell-type annotation for images with a wide range of antibody panels without requiring additional model training or human intervention. Our tool has successfully annotated over 3 million cells, revealing the spatial organization of various cell types across more than 40 different human tissues. It is open source and features a modular design, allowing for easy extension to additional cell types.

  View details for DOI 10.1016/j.cels.2025.101374

  View details for PubMedID 40925369

• Big1 is a cell cycle regulator linking cell size to basal body number. bioRxiv : the preprint server for biology Stemm-Wolf, A. J., Soh, A. W., Mitchell, L. E., Sun, H., Collet, E., Dholakia, G. L., Raju, V., Hesselberth, J. R., Taliaferro, J. M., Murphy, R. F., Heasley, L. R., Pearson, C. G. 2025

  Abstract

  Cell size control in dividing cells coordinates cell growth with cell division. In the ciliated protozoan, Tetrahymena, there is a tight link between cell size and the cytoskeletal assemblies at the cell cortex organized around basal bodies (BBs). BBs dictate the distribution of ciliary units governing cell motility and are organized into 18-22 ciliary rows. The number of BBs per cell remains remarkably consistent even when the number and lengths of ciliary rows vary. big1-1 mutant cells are large and have elevated numbers of BBs, providing a system to investigate links between BB number and cell size control. We discovered BIG1 encodes a protein with an RRM3 RNA-binding domain similar to the fission yeast meiotic entry gene, mei2. The big1-1 mutation is a predicted null allele. By extending the duration of specific cell cycle stages conducive to new BB assembly, big1-1 promotes cell size increases through BB amplification. In contrast, excess Big1 protein localizes to BBs and drives cells into premature cell division, resulting in small cells with fewer BBs. Thus, Tetrahymena Big1 localizes to BBs and controls cell cycle progression, indicating BBs and Big1 link cell growth to the cell division cycle.

  View details for DOI 10.1101/2025.07.24.666660

  View details for PubMedID 40777362

  View details for PubMedCentralID PMC12330541

• Flexible and robust cell type annotation for highly multiplexed tissue images. bioRxiv : the preprint server for biology Sun, H., Yu, S., Casals, A. M., Bäckström, A., Lu, Y., Lindskog, C., Lundberg, E., Murphy, R. F. 2024

  Abstract

  Identifying cell types in highly multiplexed images is essential for understanding tissue spatial organization. Current cell type annotation methods often rely on extensive reference images and manual adjustments. In this work, we present a tool, Robust Image-Based Cell Annotator (RIBCA), that enables accurate, automated, unbiased, and fine-grained cell type annotation for images with a wide range of antibody panels, without requiring additional model training or human intervention. Our tool has successfully annotated over 1 million cells, revealing the spatial organization of various cell types across more than 40 different human tissues. It is open-source and features a modular design, allowing for easy extension to additional cell types.

  View details for DOI 10.1101/2024.09.12.612510

  View details for PubMedID 39345395

  View details for PubMedCentralID PMC11429614