bims-gerecp Biomed News
on Gene regulatory networks of epithelial cell plasticity
Issue of 2025–06–22
eleven papers selected by
Xiao Qin, University of Oxford
  1. Perturb-Multimodal: A platform for pooled genetic screens with imaging and sequencing in intact mammalian tissue.
  2. Morphodynamics of human early brain organoid development.
  3. Organoids.
  4. scExtract: leveraging large language models for fully automated single-cell RNA-seq data annotation and prior-informed multi-dataset integration.
  5. A unified pan-cancer proteome atlas.
  6. An Overview of Analytical Approaches to Cancer Proteogenomics.
  7. Research progress of colorectal cancer in genomic and transcriptomic at multi-level.
  8. Protocol for sub-mucosal orthotopic injection of organoids into murine colon to study tumor growth and metastasis.
  9. In vivo mapping of mutagenesis sensitivity of human enhancers.
  10. Application of Organoids to Investigate Virus-Host Interactions.
  11. Rapid generation of functional vascular organoids via simultaneous transcription factor activation of endothelial and mural lineages.
  1. Cell. 2025 Jun 11. pii: S0092-8674(25)00572-0. [Epub ahead of print]
    Perturb-Multimodal: A platform for pooled genetic screens with imaging and sequencing in intact mammalian tissue.
    Reuben A Saunders, William E Allen, Xingjie Pan, Jaspreet Sandhu, Jiaqi Lu, Thomas K Lau, Karina Smolyar, Zuri A Sullivan, Catherine Dulac, Jonathan S Weissman, Xiaowei Zhuang.
      Metazoan life requires the coordinated activities of thousands of genes in spatially organized cell types. Understanding the basis of tissue function requires approaches to dissect the genetic control of diverse cellular and tissue phenotypes in vivo. Here, we present Perturb-Multimodal (Perturb-Multi), a paired imaging and sequencing method to construct large-scale, multimodal genotype-phenotype maps in tissues with pooled genetic perturbations. Using imaging, we identify perturbations in individual cells while simultaneously measuring their gene expression profiles and subcellular morphology. Using single-cell sequencing, we measure full transcriptomic responses to the same perturbations. We apply Perturb-Multi to study hundreds of genetic perturbations in the mouse liver. Our data suggest the genetic regulators and mechanisms underlying the dynamic control of hepatocyte zonation, the unfolded protein response, and steatosis. Perturb-Multi accelerates discoveries of the genetic basis of complex cell and tissue physiology and provides critical training data for emerging machine learning models of cellular function.
    Keywords:  RCA-MERFISH; hepatocyte stress response; in vivo pooled screening; lipid droplet accumulation; liver zonation; machine learning morphology; multimodal phenotyping; multiplexed RNA imaging; multiplexed protein imaging; scRNA-seq
    DOI:  https://doi.org/10.1016/j.cell.2025.05.022
  2. Nature. 2025 Jun 18.
    Morphodynamics of human early brain organoid development.
    Akanksha Jain, Gilles Gut, Fátima Sanchis-Calleja, Reto Tschannen, Zhisong He, Nicolas Luginbühl, Fides Zenk, Antonius Chrisnandy, Simon Streib, Christoph Harmel, Ryoko Okamoto, Malgorzata Santel, Makiko Seimiya, René Holtackers, Juliane K Rohland, Sophie Martina Johanna Jansen, Matthias P Lutolf, J Gray Camp, Barbara Treutlein.
      Brain organoids enable the mechanistic study of human brain development and provide opportunities to explore self-organization in unconstrained developmental systems1-3. Here we establish long-term, live light-sheet microscopy on unguided brain organoids generated from fluorescently labelled human induced pluripotent stem cells, which enables tracking of tissue morphology, cell behaviours and subcellular features over weeks of organoid development4. We provide a novel dual-channel, multi-mosaic and multi-protein labelling strategy combined with a computational demultiplexing approach to enable simultaneous quantification of distinct subcellular features during organoid development. We track actin, tubulin, plasma membrane, nucleus and nuclear envelope dynamics, and quantify cell morphometric and alignment changes during tissue-state transitions including neuroepithelial induction, maturation, lumenization and brain regionalization. On the basis of imaging and single-cell transcriptome modalities, we find that lumenal expansion and cell morphotype composition within the developing neuroepithelium are associated with modulation of gene expression programs involving extracellular matrix pathway regulators and mechanosensing. We show that an extrinsically provided matrix enhances lumen expansion as well as telencephalon formation, and unguided organoids grown in the absence of an extrinsic matrix have altered morphologies with increased neural crest and caudalized tissue identity. Matrix-induced regional guidance and lumen morphogenesis are linked to the WNT and Hippo (YAP1) signalling pathways, including spatially restricted induction of the WNT ligand secretion mediator (WLS) that marks the earliest emergence of non-telencephalic brain regions. Together, our work provides an inroad into studying human brain morphodynamics and supports a view that matrix-linked mechanosensing dynamics have a central role during brain regionalization.
    DOI:  https://doi.org/10.1038/s41586-025-09151-3
  3. Nat Biotechnol. 2025 Jun;43(6): 863
    Organoids.
      
    DOI:  https://doi.org/10.1038/s41587-025-02698-6
  4. Genome Biol. 2025 Jun 19. 26(1): 174
    scExtract: leveraging large language models for fully automated single-cell RNA-seq data annotation and prior-informed multi-dataset integration.
    Yuxuan Wu, Fuchou Tang.
      Single-cell RNA sequencing has revolutionized cellular heterogeneity research, but analyzing the abundance of unannotated public datasets remains challenging. We present scExtract, a framework leveraging large language models to automate scRNA-seq data analysis from preprocessing to annotation and integration. scExtract extracts information from research articles to guide data processing, outperforming existing reference transfer methods in benchmarks. We introduce scanorama-prior and cellhint-prior, which incorporate prior annotation information for improved batch correction while preserving biological diversities. We demonstrate scExtract's utility by integrating 14 datasets to create a comprehensive human skin atlas of 440,000 cells.
    Keywords:  Dataset integration; Large language models; Single-cell RNA sequencing
    DOI:  https://doi.org/10.1186/s13059-025-03639-x
  5. Cancer Cell. 2025 Jun 04. pii: S1535-6108(25)00221-1. [Epub ahead of print]
    A unified pan-cancer proteome atlas.
    Yang Du, Jianmin Wu.
      In this issue of Cancer Cell, Knol et al. present the Pan-Cancer Proteome Atlas (TPCPA), a proteomic resource developed using single-shot data-independent acquisition mass spectrometry (DIA-MS). TPCPA provides proteome-scale quantifications of 999 tumors across 22 cancer types in a unified manner, for discovering tumor biology, biomarkers, and therapeutic targets.
    DOI:  https://doi.org/10.1016/j.ccell.2025.05.012
  6. Methods Mol Biol. 2025 ;2921 93-118
    An Overview of Analytical Approaches to Cancer Proteogenomics.
    Chad J Creighton.
      The molecular landscape of human cancers involves multiple omics layers of complexity, from genome to proteome and beyond. Cancer proteogenomics involves the integration of protein expression patterns with somatic DNA alterations. Recently, advances in mass spectrometry-based proteomic profiling technologies have enabled the generation of combined proteomic and multi-omic data for thousands of human tumors across dozens of studies. These data in the public domain can be utilized to give us a more complete picture of cancer-specific pathways and processes and identify gene candidates for therapeutic targeting. Many proteogenomic studies are ongoing involving various cancer types according to tissue or cell of origin, including studies to predict response to therapy. In addition, pan-cancer analyses across multiple studies can identify molecular commonalities, differences, and emergent themes across tumor lineages. Data integration can determine which gene alterations at the transcriptome level are translated to the protein level. A wealth of knowledge and analytical approaches developed historically to integrate gene transcription with genomic data can be readily applied to proteogenomic analyses. Here is provided an overview of higher-level analyses of proteogenomic datasets. Such analyses include defining proteomic subtypes of cancer, exploring the impact of somatic mutations and epigenetic modifications on protein expression, cataloging proteomic correlates of more aggressive disease or drug response, and identifying enriched pathways.
    Keywords:  Cancer; Data integration; Multi-omics; Proteogenomics; Proteomics
    DOI:  https://doi.org/10.1007/978-1-0716-4502-4_5
  7. Front Genet. 2025 ;16 1533817
    Research progress of colorectal cancer in genomic and transcriptomic at multi-level.
    Qinglian Wen, Shuangyan Han, Yongxia Cui.
      Colorectal cancer is a common malignant tumor in the gastrointestinal tract, and the mechanisms of its occurrence, development, and metastasis have always been the focus of the medical community's attention. The study of CRC genetic mechanisms began with the identification of oncogenes or tumor suppressor genes and their key pathways. With further research, researchers gradually realized that single genes or pathways alone could not explain the occurrence, development, and metastasis of CRC. The development of bulk sequencing technology has helped us to analyze the occurrence, development, and metastasis mechanisms of CRC from a multi-gene, multi-pathway, and multi-dimensional perspective, but it has not brought significant benefits to the clinical treatment of tumors. The main reason for this is that bulk sequencing technology relies on homogeneous cell grouping and cannot capture the heterogeneity between cells within the tumor and the interactions within the tumor microenvironment. The development of single-cell technology has made it possible to study the mechanisms of heterogeneity between cells within CRC and the interaction within the tumor microenvironment. This review discusses the mechanisms of CRC occurrence and development in three stages: traditional molecular biology level of single gene, bulk sequencing, and single-cell sequencing. These results show that the occurrence of CRC is the result of complex interactions between genetic and non-genetic factors in somatic cell evolution, where the heterogeneity between cells within the tumor and the tumor microenvironment are crucial for CRC progression.
    Keywords:  CRC (colorectal cancer); evolutionary genomics; single-cell genomics; tumor heterogeneity; tumor microenvironment
    DOI:  https://doi.org/10.3389/fgene.2025.1533817
  8. STAR Protoc. 2025 Jun 12. pii: S2666-1667(25)00293-X. [Epub ahead of print]6(2): 103887
    Protocol for sub-mucosal orthotopic injection of organoids into murine colon to study tumor growth and metastasis.
    Sura Atatri, Marianne Meyers, Eliane Klein, Valentina Brunner, Markus Tschurtschenthaler, Elisabeth Letellier.
      Orthotopic mouse models of colorectal cancer (CRC) better recapitulate the physiological processes of tumor development and metastatic dissemination. Here, we provide a protocol for colonoscopy-guided transplantation of organoids into the murine colon. We describe the steps for preparing mouse organoids, equipment, and mice for injections, as well as performing colonoscopy-guided mucosal injections and providing subsequent care. This model can be used to investigate various experimental setups, including survival, metastatic potential, and the effects of treatments. For complete details on the use and execution of this protocol, please refer to Felchle et al.1.
    Keywords:  Cancer; Health Sciences; Model Organisms; Organoids
    DOI:  https://doi.org/10.1016/j.xpro.2025.103887
  9. Nature. 2025 Jun 18.
    In vivo mapping of mutagenesis sensitivity of human enhancers.
    Michael Kosicki, Boyang Zhang, Vivian Hecht, Anusri Pampari, Laura E Cook, Neil Slaven, Jennifer A Akiyama, Ingrid Plajzer-Frick, Catherine S Novak, Momoe Kato, Stella Tran, Riana D Hunter, Kianna von Maydell, Sarah Barton, Erik Beckman, Yiwen Zhu, Diane E Dickel, Anshul Kundaje, Axel Visel, Len A Pennacchio.
      Distant-acting enhancers are central to human development1. However, our limited understanding of their functional sequence features prevents the interpretation of enhancer mutations in disease2. Here we determined the functional sensitivity to mutagenesis of human developmental enhancers in vivo. Focusing on seven enhancers that are active in the developing brain, heart, limb and face, we created over 1,700 transgenic mice for over 260 mutagenized enhancer alleles. Systematic mutation of 12-base-pair blocks collectively altered each sequence feature in each enhancer at least once. We show that 69% of all blocks are required for normal in vivo activity, with mutations more commonly resulting in loss (60%) than in gain (9%) of function. Using predictive modelling, we annotated critical nucleotides at the base-pair resolution. The vast majority of motifs predicted by these machine learning models (88%) coincided with changes in in vivo function, and the models showed considerable sensitivity, identifying 59% of all functional blocks. Taken together, our results reveal that human enhancers contain a high density of sequence features that are required for their normal in vivo function and provide a rich resource for further exploration of human enhancer logic.
    DOI:  https://doi.org/10.1038/s41586-025-09182-w
  10. Methods Mol Biol. 2025 ;2940 141-150
    Application of Organoids to Investigate Virus-Host Interactions.
    Tong Wu, Quan Zhou, Chunfu Zheng, Xiaodong Zou.
      Complex interactions between viruses and host cells are difficult to study via traditional models. Organoids, three-dimensional (3D) tissue-like structures derived from stem cells, have emerged as transformative tools for modeling human tissues and revealing the intricate dynamics of virus-host interactions. This chapter summarizes the relevant applications of organoids in virus-host interaction studies and provides detailed information and experimental procedures for using them to study virus-host interactions.
    Keywords:  Applications; Organoids; Virus–host interactions
    DOI:  https://doi.org/10.1007/978-1-0716-4615-1_13
  11. Cell Stem Cell. 2025 Jun 10. pii: S1934-5909(25)00221-8. [Epub ahead of print]
    Rapid generation of functional vascular organoids via simultaneous transcription factor activation of endothelial and mural lineages.
    Liyan Gong, Yadong Zhang, Yonglin Zhu, Umji Lee, Allen Chilun Luo, Xiang Li, Xi Wang, Danyang Chen, William T Pu, Ruei-Zeng Lin, Minglin Ma, Miao Cui, Kaifu Chen, Kai Wang, Juan M Melero-Martin.
      Vascular organoids (VOs) are valuable tools for studying vascular development, disease, and regenerative medicine. However, controlling endothelial and mural compartments independently remains challenging. Here, we present a streamlined method to generate VOs from induced pluripotent stem cells (iPSCs) via orthogonal activation of the transcription factors (TFs) ETV2 and NKX3.1 using Dox-inducible or modRNA systems. This approach enables efficient co-differentiation of endothelial cells (iECs) and mural cells (iMCs), producing functional 3D VOs in 5 days without ECM embedding. VOs matured further upon ECM exposure, forming larger, structured vessels. Single-cell RNA sequencing revealed vascular heterogeneity, and temporal regulation of TF expression allowed modulation of arterial and angiogenic iEC phenotypes. In vivo, VOs engrafted into immunodeficient mice, formed perfused vasculature, and promoted revascularization in models of hind limb ischemia and pancreatic islet transplantation. These findings establish a rapid and versatile VO platform with broad potential for vascular modeling, disease studies, and regenerative cell therapy.
    Keywords:  blood vessels organoids; endothelial cells; iPSCs; ischemia models; mural cells; pluripotent stem cells; therapeutic vascularization; transcription factor induction; vascular differentiation; vascular organoids
    DOI:  https://doi.org/10.1016/j.stem.2025.05.014
This page is being maintained by Thomas Krichel. It was last updated on 2025‒06‒24 at 15:13.