Huangqingbo Sun

All Publications

• 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