bims-gerecp Biomed News
on Gene regulatory networks of epithelial cell plasticity
Issue of 2025–10–26
twenty papers selected by
Xiao Qin, University of Oxford
  1. scooby: modeling multimodal genomic profiles from DNA sequence at single-cell resolution.
  2. CANDiT: A machine learning framework for differentiation therapy in colorectal cancer.
  3. PHLOWER leverages single-cell multimodal data to infer complex, multi-branching cell differentiation trajectories.
  4. Active learning framework leveraging transcriptomics identifies modulators of disease phenotypes.
  5. Insights, opportunities, and challenges provided by large cell atlases.
  6. Single-cell and spatial transcriptomics integration: new frontiers in tumor microenvironment and cellular communication.
  7. Multidimensional decoding of colorectal cancer heterogeneity: Artificial intelligence-enabled precision exploration of single-cell and spatial transcriptomics.
  8. Regulated cell death in cancer: Mechanisms, crosstalk, and opportunities for therapy.
  9. Enhancer activation from transposable elements in extrachromosomal DNA.
  10. Cell Decoder: decoding cell identity with multi-scale explainable deep learning.
  11. Google AI aims to make best-in-class scientific software even better.
  12. p53 drives lung cancer regression through a TSC2/TFEB-dependent senescence program.
  13. Four game-changing immunology tools to watch.
  14. Revisiting the somatic mutation theory of cancer pathogenesis.
  15. Pancreatic cancer relies on opposing signalling pathways to drive its cellular diversity.
  16. Tissue and cellular spatiotemporal dynamics in colon aging.
  17. AI chatbots are sycophants - researchers say it's harming science.
  18. Intestinal LKB1 Loss Drives a Premalignant Program Along the Serrated Cancer Pathway.
  19. Phenotypic plasticity as the foundation of lifelong development.
  20. Proteases in intestinal health and disease.
  1. Nat Methods. 2025 Oct 22.
    scooby: modeling multimodal genomic profiles from DNA sequence at single-cell resolution.
    Johannes C Hingerl, Laura D Martens, Alexander Karollus, Trevor Manz, Jason D Buenrostro, Fabian J Theis, Julien Gagneur.
      Understanding how regulatory sequences shape gene expression across individual cells is a fundamental challenge in genomics. Joint RNA sequencing and epigenomic profiling provides opportunities to build models capturing sequence determinants across steps of gene expression. However, current models, developed primarily for bulk omics data, fail to capture the cellular heterogeneity and dynamic processes revealed by single-cell multimodal technologies. Here, we introduce scooby, a framework to model genomic profiles of single-cell RNA-sequencing coverage and single-cell assay for transposase-accessible chromatin using sequencing insertions from sequence at single-cell resolution. For this, we leverage the pretrained multiomics profile predictor Borzoi and equip it with a cell-specific decoder. Scooby recapitulates cell-specific expression levels of held-out genes and identifies regulators and their putative target genes. Moreover, scooby allows resolving single-cell effects of bulk expression quantitative trait loci and delineating their impact on chromatin accessibility and gene expression. We anticipate scooby to aid unraveling the complexities of gene regulation at the resolution of individual cells.
    DOI:  https://doi.org/10.1038/s41592-025-02854-5
  2. Cell Rep Med. 2025 Oct 20. pii: S2666-3791(25)00494-X. [Epub ahead of print] 102421
    CANDiT: A machine learning framework for differentiation therapy in colorectal cancer.
    Saptarshi Sinha, Joshua Alcantara, Kevin Perry, Vanessa Castillo, Annelies K Ondersma, Satarupa Banerjee, Ella McLaren, Celia R Espinoza, Sahar Taheri, Eleadah Vidales, Courtney Tindle, Adel Adel, Siamak Amirfakhri, Joseph R Sawires, Jerry Yang, Michael Bouvet, Pradipta Ghosh.
      Reactivating lineage commitment to differentiate, and hence eliminate, cancer stem cells (CSCs) remains a therapeutic challenge. Here, we present CANDiT (cancer-associated nodes for differentiation targeting), a machine learning framework that identifies transcriptomic vulnerabilities for differentiation therapy in colorectal cancer (CRC). Centering on CDX2-a master intestinal lineage factor lost in high-risk, poorly differentiated CRCs-we identify PRKAB1, a stress polarity sensor, as a top therapeutic target. A clinical-grade PRKAB1 agonist reactivates lineage programs, dismantles Wnt/YAP-driven stemness, and selectively eliminates CDX2-low CSCs across CRC cell lines, xenografts, and patient-derived organoids (PDOs). Multivariate analysis reveals a strong therapeutic index tied to the CDX2-low state. A 50-gene response signature, derived from integrated modeling across all platforms, predicts ∼50% reduction in recurrence and mortality risk. Like immunotherapy, CANDiT resurrects a physiologic program-differentiation-to selectively eliminate CSCs, offering a scalable, precision framework for lineage restoration in solid tumors.
    Keywords:  CCDC88A; CDX2 restoration; SPS; cancer stem cell; differentiation therapy; stress-polarity pathway
    DOI:  https://doi.org/10.1016/j.xcrm.2025.102421
  3. Nat Methods. 2025 Oct 23.
    PHLOWER leverages single-cell multimodal data to infer complex, multi-branching cell differentiation trajectories.
    Mingbo Cheng, Jitske Jansen, Katharina C Reimer, Vincent P Grande, James S Nagai, Zhijian Li, Paul Kießling, Martin Grasshoff, Christoph Kuppe, Michael T Schaub, Rafael Kramann, Ivan G Costa.
      Computational trajectory analysis is a key computational task for inferring differentiation trees from this single-cell data. An open challenge is the prediction of complex and multi-branching trees from multimodal data. To address these challenges, we present PHLOWER (decomposition of the Hodge Laplacian for inferring trajectories from flows of cell differentiation), which leverages the harmonic component of the Hodge decomposition on simplicial complexes to infer trajectory embeddings from single-cell multimodal data. These natural representations of cell differentiation facilitate the estimation of their underlying differentiation trees. We evaluate PHLOWER through benchmarking with multi-branching differentiation trees and using kidney organoid multimodal and spatial single-cell data. These demonstrate the power of PHLOWER in both the inference of complex trees and the identification of transcription factors regulating off-target cells in kidney organoids. Thus, PHLOWER enables inference of complex branching trajectories and prediction of transcriptional regulators by leveraging multimodal data.
    DOI:  https://doi.org/10.1038/s41592-025-02870-5
  4. Science. 2025 10 23. eadi8577
    Active learning framework leveraging transcriptomics identifies modulators of disease phenotypes.
    Benjamin DeMeo, Charlotte Nesbitt, Samuel A Miller, Daniel B Burkhardt, Inna Lipchina, Doris Fu, Peter Holderrieth, David Kim, Sergey Kolchenko, Artur Szalata, Ishan Gupta, Christine Kerr, Thomas Pfefer, Raziel Rojas-Rodriguez, Sunil Kuppassani, Laurens Kruidenier, Parul B Doshi, Mahdi Zamanighomi, James J Collins, Alex K Shalek, Fabian J Theis, Mauricio Cortes.
      Phenotypic drug screening remains constrained by the vastness of chemical space and technical challenges scaling experimental workflows. To overcome these barriers, computational methods have been developed to prioritize compounds, but they rely on either single-task models lacking generalizability or heuristic-based genomic proxies that resist optimization. We designed an active deep-learning framework that leverages omics to enable scalable, optimizable identification of compounds that induce complex phenotypes. Our generalizable algorithm outperformed state-of-the-art models on classical recall, translating to a 13-17x increase in phenotypic hit-rate across two hematological discovery campaigns. Combining this algorithm with a lab-in-the-loop signature refinement step, we achieved an additional two-fold increase in hit-rate and molecular insights. In sum, our framework enables efficient phenotypic hit identification campaigns, with broad potential to accelerate drug discovery.
    DOI:  https://doi.org/10.1126/science.adi8577
  5. Genome Biol. 2025 Oct 20. 26(1): 358
    Insights, opportunities, and challenges provided by large cell atlases.
    Martin Hemberg, Federico Marini, Shila Ghazanfar, Ahmad Al Ajami, Najla Abassi, Benedict Anchang, Bérénice A Benayoun, Yue Cao, Ken Chen, Yesid Cuesta-Astroz, Zachary DeBruine, Calliope A Dendrou, Iwijn De Vlaminck, Katharina Imkeller, Ilya Korsunsky, Alex R Lederer, Jessica Jingyi Li, Pieter Meysman, Clint L Miller, Kerry A Mullan, Uwe Ohler, Pratibha Panwar, Nikolaos Patikas, Jonas Schuck, Jacqueline H Y Siu, Timothy J Triche, Alex Tsankov, Sander W van der Laan, Masanao Yajima, Jean Yang, Fabio Zanini, Ivana Jelic.
      The field of single-cell biology is growing rapidly, generating large amounts of data from a variety of species, disease conditions, tissues, and organs. Coordinated efforts such as CZI CELLxGENE, HuBMAP, Broad Institute Single Cell Portal, and DISCO allow researchers to access large volumes of curated datasets, including more than just scRNA-seq data. These resources have created an opportunity to build and expand the computational biology ecosystem to develop tools necessary for data reuse and for extracting novel biological insights. We highlight achievements made so far, areas where further development is needed, and specific challenges that need to be overcome.
    DOI:  https://doi.org/10.1186/s13059-025-03771-8
  6. Front Immunol. 2025 ;16 1649468
    Single-cell and spatial transcriptomics integration: new frontiers in tumor microenvironment and cellular communication.
    Wenxin Shi, Zhiqiang Zhang, Xiaotong Xu, Yanpeng Tian, Li Feng, Xianghua Huang, Yanfang Du, Zhongkang Li.
      Single-cell RNA sequencing (scRNA-seq) has emerged as an advanced biological technology capable of resolving the complexity of cancer landscapes at single-cell resolution. Spatial transcriptomics(ST), as an innovative complementary approach, effectively compensates for the lack of spatial information inherent in scRNA-seq data. This review explores the rapidly evolving integration of scRNA-seq and ST and their transformative role in deciphering the tumor microenvironment (TME). We highlight how these technologies jointly uncover cellular heterogeneity, stromal-immune interactions, and spatial niches driving tumor progression and therapy resistance. Moving beyond previous reviews, we emphasize emerging computational strategies for data integration-including deconvolution and mapping approaches-and evaluate their applications in characterizing immune evasion, fibroblast diversity, and cell-cell communication networks. Ultimately, this review provides a forward-looking perspective on how spatial multi-omics are poised to advance precision oncology through spatially-informed biomarkers and diagnostic tools. We conclude that the full clinical potential of these technologies relies on closing the gap between analytical innovation and robust clinical implementation.
    Keywords:  cancer heterogeneity; intercellular communication; single-cell RNA sequencing; spatial transcriptomics; tumor microenvironment
    DOI:  https://doi.org/10.3389/fimmu.2025.1649468
  7. World J Gastrointest Oncol. 2025 Oct 15. 17(10): 110661
    Multidimensional decoding of colorectal cancer heterogeneity: Artificial intelligence-enabled precision exploration of single-cell and spatial transcriptomics.
    Wen-Yu Luan, Qi Zhao, Zheng Zhang, Zhen-Xi Xu, Si-Xiang Lin, Yan-Dong Miao.
      As a common malignant tumor, the heterogeneity of colorectal cancer plays an important role in tumor progression and treatment response. In recent years, the rapid development of single-cell transcriptomics and spatial transcriptomics technologies has provided new perspectives for resolving the heterogeneity of colorectal cancer. These techniques can reveal the complexity of cellular composition and their interactions in the tumor microenvironment, and thus facilitate a deeper understanding of tumor biology. However, in practical applications, researchers still face technical challenges such as data processing and result interpretation. The aim of this paper is to explore how to use artificial intelligence (AI) technology to enhance the research efficiency of single-cell and spatial transcriptomics, analyze the current research progress and its limitations, and explore how combining AI approaches can provide new ideas for decoding the heterogeneity of colorectal cancer, and ultimately provide theoretical basis and practical guidance for the clinical precision treatment.
    Keywords:  Artificial intelligence; Colorectal cancer; Single-cell transcriptomics; Spatial transcriptomics; Tumor heterogeneity
    DOI:  https://doi.org/10.4251/wjgo.v17.i10.110661
  8. Cancer Lett. 2025 Oct 21. pii: S0304-3835(25)00649-4. [Epub ahead of print]635 218077
    Regulated cell death in cancer: Mechanisms, crosstalk, and opportunities for therapy.
    Yimei Meng, Qun Chen, Zhijun Zhou, Min Li.
      Regulated cell death (RCD) is a fundamental biological process essential for tissue homeostasis, and the elimination of damaged or malignant cells. In cancer, dysregulation of RCD is closely linked to tumor initiation, progression, therapeutic resistance, and remodeling of the tumor microenvironment (TME). In this review, we classify RCD in cancer into three broad groups. Classical cell death types include apoptosis, autophagy, necroptosis, and pyroptosis, which have well-established roles in controlling cell fate. Metal-dependent pathways, represented by ferroptosis, and cuproptosis, highlight vulnerabilities linked to iron and copper metabolism. Emerging modalities such as entosis, NETosis, disulfidptosis, and parthanatos, further expand the conceptual landscape of RCD, revealing diverse mechanisms by which cancer cells respond to stress. We synthesize the molecular mechanisms and signaling networks governing these processes, emphasizing their intricate crosstalk, shared regulators, and context-dependent dual roles in tumor suppression and promotion. Finally, we discuss translational strategies to exploit RCD, including pharmacologic modulators, nanomaterial-based approaches, and early clinical evidence, outlining future directions for precision oncology. Together, these insights establish RCD as a dynamic and targetable network that provides both mechanistic understanding and opportunities for novel therapeutic interventions in cancer.
    Keywords:  Drug delivery; Immune evasion; Metabolism; Precision oncology; Programmed cell death
    DOI:  https://doi.org/10.1016/j.canlet.2025.218077
  9. Nat Cell Biol. 2025 Oct 21.
    Enhancer activation from transposable elements in extrachromosomal DNA.
    Katerina Kraft, Sedona E Murphy, Matthew G Jones, Quanming Shi, Aarohi Bhargava-Shah, Christy Luong, King L Hung, Britney J He, Rui Li, Seung Kuk Park, Michael T Montgomery, Natasha E Weiser, Yanbo Wang, Jens Luebeck, Vineet Bafna, Jef D Boeke, Paul S Mischel, Alistair N Boettiger, Howard Y Chang.
      Extrachromosomal DNA (ecDNA) drives oncogene amplification and intratumoural heterogeneity in aggressive cancers. While transposable element reactivation is common in cancer, its role on ecDNA remains unexplored. Here we map the 3D architecture of MYC-amplified ecDNA in colorectal cancer cells and identify 68 ecDNA-interacting elements-genomic loci enriched for transposable elements that are frequently integrated onto ecDNA. We focus on an L1M4a1#LINE/L1 fragment co-amplified with MYC, which functions only in the ecDNA-amplified context. Using CRISPR-CATCH, CRISPR interference and reporter assays, we confirm its presence on ecDNA, enhancer activity and essentiality for cancer cell fitness. These findings reveal that repetitive elements can be reactivated and co-opted as functional rather than inactive sequences on ecDNA, potentially driving oncogene expression and tumour evolution. Our study uncovers a mechanism by which ecDNA harnesses repetitive elements to shape cancer phenotypes, with implications for diagnosis and therapy.
    DOI:  https://doi.org/10.1038/s41556-025-01788-6
  10. Genome Biol. 2025 Oct 20. 26(1): 359
    Cell Decoder: decoding cell identity with multi-scale explainable deep learning.
    Jun Zhu, Zeyang Zhang, Yujia Xiang, Beini Xie, Xinwen Dong, Linhai Xie, Peijie Zhou, Rongyan Yao, Xiaowen Wang, Yang Li, Fuchu He, Wenwu Zhu, Ziwei Zhang, Cheng Chang.
       BACKGROUND: Cells are the fundamental units of life, and understanding their diversity and functionality requires detailed characterization. The rise of single-cell omics data enables this, yet current deep learning approaches lack multi-scale interpretability.
    RESULTS: We introduce Cell Decoder, a model that integrates biological prior knowledge to provide a multi-scale representation of cells. Using automated machine learning and post hoc analysis, Cell Decoder decodes cell identity and outperforms existing methods. It offers multi-view interpretability and facilitates data integration.
    CONCLUSIONS: Applied to human bone and mouse embryonic data, Cell Decoder reveals the multi-scale heterogeneity of cell identities, providing a powerful framework for advancing our understanding of cellular diversity.
    DOI:  https://doi.org/10.1186/s13059-025-03832-y
  11. Nature. 2025 Oct 22.
    Google AI aims to make best-in-class scientific software even better.
    Matthew Hutson.
      
    Keywords:  Computational biology and bioinformatics; Computer science; Machine learning; Technology
    DOI:  https://doi.org/10.1038/d41586-025-03289-w
  12. Cancer Discov. 2025 Oct 21.
    p53 drives lung cancer regression through a TSC2/TFEB-dependent senescence program.
    Mengxiong Wang, Kathryn T Bieging-Rolett, Alyssa M Kaiser, Colleen A Brady, John H Lockhart, Sofia Ferreira, Kha T Nguyen, Arati Rajeevan, Simone A Evans, Tianyu Zhao, Nitin Raj, Arielle Elkrief, Sam E Tischfield, Marc Ladanyi, Michael G Ozawa, Nam Q Bui, Christopher T Chen, Elsa R Flores, Laura D Attardi.
      Pharmacological restoration of p53 tumor suppressor function is a conceptually appealing therapeutic strategy for the many deadly cancers with compromised p53 activity, including lung adenocarcinoma (LUAD). However, the p53 pathway has remained undruggable, partly because of insufficient understanding of how to drive effective therapeutic responses without toxicity. Here, we use mouse and human models to deconstruct the transcriptional programs and sequelae underlying robust therapeutic responses in LUAD. We show that p53 drives potent tumor regression by direct Tsc2 transactivation, leading to mTORC1 inhibition and TFEB nuclear accumulation, which in turn triggers lysosomal gene expression programs, autophagy, and cellular senescence. Senescent LUAD cells secrete factors to recruit macrophages, precipitating cancer cell phagocytosis and tumor regression. Collectively, our analyses reveal a surprisingly complex cascade of events underlying a p53 therapeutic response in LUAD and illuminate targetable nodes for p53 combination therapies, thus establishing a critical framework for optimizing p53-based therapeutics.
    DOI:  https://doi.org/10.1158/2159-8290.CD-25-0525
  13. Nature. 2025 Oct;646(8086): S30-S32
    Four game-changing immunology tools to watch.
    Gemma Conroy.
      
    Keywords:  Biological techniques; CRISPR-Cas9 genome editing; Genomics; Immunology; Transcriptomics
    DOI:  https://doi.org/10.1038/d41586-025-03335-7
  14. Nat Rev Genet. 2025 Oct 22.
    Revisiting the somatic mutation theory of cancer pathogenesis.
    Jean Fan.
      
    DOI:  https://doi.org/10.1038/s41576-025-00905-3
  15. Nature. 2025 Oct 22.
    Pancreatic cancer relies on opposing signalling pathways to drive its cellular diversity.
    Marc P Stemmler.
      
    Keywords:  Cancer; Medical research
    DOI:  https://doi.org/10.1038/d41586-025-03133-1
  16. Nat Biotechnol. 2025 Oct 22.
    Tissue and cellular spatiotemporal dynamics in colon aging.
    Aidan C Daly, Francesco Cambuli, Tarmo Äijö, Britta Lötstedt, Nemanja Despot Marjanovic, Sara Fernandez, Olena Kuksenko, Matthew Smith-Erb, Daniel Domovic, Nicholas Van Wittenberghe, Eugene Drokhlyansky, Gabriel K Griffin, Hemali Phatnani, Richard Bonneau, Aviv Regev, Sanja Vickovic.
      Tissue structure and molecular circuitry in the colon can be profoundly impacted by systemic age-related effects but many of the underlying molecular cues remain unclear. Here, we build a cellular and spatial atlas of the colon across three anatomical regions and 11 age groups, encompassing ~1,500 mouse gut tissues profiled by spatial transcriptomics and ~400,000 single nucleus RNA-sequencing profiles. We develop a computational framework, cSplotch, which learns a hierarchical Bayesian model of spatially resolved cellular expression associated with age, tissue region and sex by leveraging histological features to share information across tissue samples and data modalities. Using this model, we identify cellular and molecular gradients along the adult colonic tract and across the main crypt axis and multicellular programs associated with aging in the large intestine. Our multimodal framework for the investigation of cell and tissue organization can aid in the understanding of cellular roles in tissue-level pathology.
    DOI:  https://doi.org/10.1038/s41587-025-02830-6
  17. Nature. 2025 Oct 24.
    AI chatbots are sycophants - researchers say it's harming science.
    Miryam Naddaf.
      
    Keywords:  Research data; Technology
    DOI:  https://doi.org/10.1038/d41586-025-03390-0
  18. Gastroenterology. 2025 Oct 23. pii: S0016-5085(25)05850-0. [Epub ahead of print]
    Intestinal LKB1 Loss Drives a Premalignant Program Along the Serrated Cancer Pathway.
    S F Plugge, H Ma, J Y van der Vaart, J Sprangers, F H M Morsink, D Xanthakis, C Jamieson, K B W Stroot, A R Keijzer, T Margaritis, T Candelli, R Straver, J de Ridder, F C P Holstege, W W J de Leng, G J A Offerhaus, A Merenda, M M Maurice.
       BACKGROUND & AIMS: Heterozygous inactivating mutations of Serine Threonine Kinase 11/Liver Kinase B1 (LKB1) are causative to the Peutz-Jeghers syndrome (PJS), a hereditary disease characterized by gastrointestinal hamartomatous polyposis and increased cancer susceptibility. Although LKB1 loss-induced polyp formation has been ascribed to nonepithelial tissues, how LKB1 deficiency increases cancer risk of patients by altering the phenotypical landscape and hierarchical organization of epithelial tissues remains poorly understood.
    METHODS: Using CRISPR/Cas9, we generated heterozygous and homozygous Lkb1-deficient mouse small intestinal and human colon organoids. These organoids were characterized by an integrated approach that combines imaging, bulk and single-cell RNA sequencing, and growth factor dependency assays. Our findings were validated in human PJS-derived tissues using immunohistochemistry and linked to colorectal cancer profiles using the Cancer Genome Atlas (TCGA) cancer database.
    RESULTS: Our results reveal that heterozygous Lkb1 loss is sufficient to push intestinal cells into a premalignant transcriptional program associated with serrated colorectal cancer, which is further amplified by loss of heterozygosity. This altered epithelial growth state associates with persistent features of regeneration and enhanced EGFR ligand and receptor expression, conferring niche-independent growth properties to Lkb1-deficient organoids. Moreover, our newly generated LKB1-mutant signature is enriched in sporadic serrated colorectal cancer, and synergistic cooperation of Lkb1 deficiency with mutant Kras was experimentally confirmed by assessing organoid growth properties and transcriptomes.
    CONCLUSIONS: Heterozygous loss of LKB1 pushes intestinal cells into a chronic regenerative state, which is amplified on loss of heterozygosity. Lkb1 deficiency thereby generates fertile ground for serrated colorectal cancer formation in the intestine, potentially explaining the increased cancer risk observed in PJS.
    Keywords:  Colorectal Cancer; LKB1; Organoids; Peutz-Jeghers Syndrome; Regeneration; Serrated Tumors
    DOI:  https://doi.org/10.1053/j.gastro.2025.07.041
  19. Development. 2025 Oct 15. pii: dev205126. [Epub ahead of print]152(20):
    Phenotypic plasticity as the foundation of lifelong development.
    Mohannad Dardiry, Aissam Ikmi.
      Many animals retain the capacity to transform their form and function throughout life, yet developmental biology has predominantly focused on early stages. Non-bilaterian animals, in particular, offer opportunities to investigate the principles underlying lifelong development, including regeneration, asexual reproduction, morphological plasticity and reverse development. We examine these transformations through the lens of phenotypic plasticity, presenting a modular framework that highlights how environmental cues trigger developmental programs. This framework supports a conceptual shift from viewing development as a terminal process to one of dynamic navigation through stable yet responsive organismal states, positioning non-bilaterian metazoans as key models for understanding lifelong developmental competence.
    Keywords:  Developmental plasticity; Life cycle plasticity; Morphological plasticity; Non-bilaterians; Reverse development; Whole-body regeneration
    DOI:  https://doi.org/10.1242/dev.205126
  20. Nat Rev Gastroenterol Hepatol. 2025 Oct 20.
    Proteases in intestinal health and disease.
    Celine Deraison, Nathalie Vergnolle.
      Extracellular proteases, originating from the host or the microbiota, are key signalling molecules involved in cellular communication with the environment. They signal through a wide array of mechanisms, ranging from receptor activation to protein transformation and even degradation. Protease signals are irreversible, as it involves the cleavage of proteins. Therefore, proteases are tightly controlled, and must be understood within the context of the complex networks in which they operate - their activity is tightly regulated by access to specific substrates and the presence of inhibitors. The intestine is particularly exposed to extracellular proteases, which have major roles in gut physiology: digestion, food antigen processing, barrier function, epithelial renewal and microbiome homeostasis. Dysregulated proteolytic balance is associated with intestinal pathologies including inflammatory bowel disease, irritable bowel syndrome, coeliac disease and colorectal cancer. Extracellular proteases are major contributors to a number of gut dysfunctions, including microbiota dysbiosis, barrier dysfunction, matrix remodelling, activation of mucosal immunity and nociceptive or motility abnormalities. Consequently, proteolytic homeostasis at the intestinal mucosa surface has become a goal for intestinal health, and new therapeutic options targeting the interplay among proteases, their inhibitors and their substrates have been explored.
    DOI:  https://doi.org/10.1038/s41575-025-01129-w
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