bims-gerecp Biomed News
on Gene regulatory networks of epithelial cell plasticity
Issue of 2026–02–15
seventeen papers selected by
Xiao Qin, University of Oxford
  1. Dissecting reversible and irreversible single cell state transitions from gene regulatory networks.
  2. Enhancer dynamics and cellular architecture in the human spinal cord.
  3. Multichannel genomic recording of biological information with ENGRAM.
  4. Engineered intestinal crypt geometry uncovers YAP1-dependent fetal-to-adult transition.
  5. Metabolic permissiveness: how tissue context shapes cancer.
  6. Massively parallel reporter assays: from barcodes to biology.
  7. Epithelial Reprogramming and Transition during Pulmonary Bioengineering.
  8. Deep-coverage, high-throughput single-cell metabolomics.
  9. Protocol for lentiviral engineering and multi-omic characterization of human kidney tubuloids.
  10. Epigenetic Gatekeeping of Intestinal Stem Cell Transformation.
  11. Applications of AI to single-cell and spatial transcriptomics: current state-of-the-art and challenges.
  12. AI Co-Scientists Move to the Front Lines of Cancer Research.
  13. Early microglial priming in Alzheimer's disease revealed by ME-seq.
  14. Extrachromosomal DNA drives cancer evolution.
  15. The Role of Fibroblast-Epithelial Cross-Talk on the Distribution of Distinct Fibroblast Phenotypes in the Intestinal Crypt.
  16. Single-Cell Atlas of Transcription and Chromatin States Reveals Regulatory Programs in the Human Brain.
  17. Multiplexed enrichment and tracking of lineages with CloneSweeper.
  1. Mol Syst Biol. 2026 Feb 09.
    Dissecting reversible and irreversible single cell state transitions from gene regulatory networks.
    Daniel A Ramirez, Mingyang Lu.
      Understanding cell state transitions and their governing regulatory mechanisms remains one of the fundamental questions in biology. We develop a computational method, state transition inference using cross-cell correlations (STICCC), for predicting reversible and irreversible cell state transitions at single-cell resolution by using gene expression data and a set of gene regulatory interactions. The method is inspired by the fact that the gene expression time delays between regulators and targets can be exploited to infer past and future gene expression states. From applications to both simulated and experimental single-cell gene expression data, we show that STICCC-inferred vector fields capture basins of attraction and irreversible fluxes. By connecting regulatory information with systems' dynamical behaviors, STICCC reveals how network interactions influence reversible and irreversible state transitions. Compared to existing methods that infer pseudotime and RNA velocity, STICCC provides complementary insights into the gene regulation of cell state transitions.
    Keywords:  Cell State Transition; Gene Regulatory Network (GRN); RNA Velocity; Single Cell RNA-seq; Systems Biology
    DOI:  https://doi.org/10.1038/s44320-026-00196-8
  2. Neuron. 2026 Feb 12. pii: S0896-6273(25)00991-2. [Epub ahead of print]
    Enhancer dynamics and cellular architecture in the human spinal cord.
    Elena K Kandror, Mathieu Carriere, Alexis Peterson, Will Liao, Andreas Tjärnberg, Jun Hou Fung, Krishnaa T Mahbubani, Jackson Loper, William Pangburn, Yuchen Xu, Kourosh Saeb-Parsy, Tom Maniatis, Abbas H Rizvi.
      Studies of neurodegenerative disease mechanisms require an understanding of the cellular complexity of the healthy human spinal cord. Here, we report the spatial organization of RNA transcription and associated enhancer dynamics in the adult human spinal cord at single-cell and single-molecule resolution. We expand traditional multi-omic measurements and identify epigenetically poised and bivalent active transcriptional enhancer states that define cell-type specification. Simultaneous detection of chromatin accessibility and histone modifications in spinal cord nuclei reveals previously unobserved cell-type-specific masked enhancer activity, in which transcriptional activation is uncoupled from chromatin accessibility. Such masked enhancers define both stable cell-type identity and transitions between cells undergoing differentiation. We also define gene regulatory networks in glial cells that reorganize along the rostrocaudal axis, demonstrating anatomical differences in gene regulation. Finally, we identify the spatial organization of cells into distinct cellular networks and address the functional significance of this observation in the context of paracrine signaling. We conclude that cellular diversity in the spinal cord is best captured through the lens of enhancer state and intercellular interactions that drive transitions in cellular state.
    Keywords:  computational biology; enhancer dynamics; gene regulation; multiomics; single-nucleus epigenomics; spatial transcriptomics; spinal cord
    DOI:  https://doi.org/10.1016/j.neuron.2025.12.035
  3. Nat Protoc. 2026 Feb 11.
    Multichannel genomic recording of biological information with ENGRAM.
    Jenny F Nathans, Troy A McDiarmid, Wei Chen, Jay Shendure.
      Molecular recording is an emerging paradigm for measuring biology over time. Enhancer-mediated genomic recording of activity in multiplex (ENGRAM) is a recently described synthetic biology circuit architecture that converts the transient activity of cis-regulatory elements (CREs) into stable genomic records that can be retrospectively recovered via DNA sequencing. Here we provide a step-by-step protocol for conducting ENGRAM experiments and analyzing the resulting data. We also describe key design considerations for ENGRAM recorders, summarize the strengths and limitations of ENGRAM, and highlight applications, including multiplex signal recording and high-throughput CRE screening. In contrast to other systems for DNA-based recording in mammalian systems, ENGRAM relies on prime editing-mediated insertions to record the activity of a given CRE, such that it is inherently multiplexable-for example, four-base-pair insertions can represent the activities of up to 256 distinct CREs. A further contrast lies with ENGRAM's compatibility with DNA Typewriter, which facilitates the capture of signal order. For users with basic skills in molecular biology, mammalian cell culture and DNA sequencing analysis, ENGRAM experiments can typically be completed within 5-6 weeks.
    DOI:  https://doi.org/10.1038/s41596-025-01322-w
  4. Cell Stem Cell. 2026 Feb 12. pii: S1934-5909(26)00029-9. [Epub ahead of print]
    Engineered intestinal crypt geometry uncovers YAP1-dependent fetal-to-adult transition.
    Martti Maimets, Mikhail Nikolaev, Cecilia Lövkvist, Fabien Bertillot, Hjalte List Larsen, Raul Bardini Bressan, Antonios Georgantzoglou, Nikolce Gjorevski, Eirini Filidou, Maureen Zøylner, Stine Lind Hansen, Astrid M Baattrup, Isidora Banjac, Jordi Guiu, Sara A Wickström, Matthias P Lutolf, Kim B Jensen.
      During morphogenesis, the intestine undergoes significant structural remodeling, transitioning from a simple tube of immature epithelium into a complex crypt-villus architecture housing mature cell types. However, the relationship between these structural changes and epithelial maturation has remained enigmatic. Using engineered scaffolds that replicate crypt-like geometries, we establish a robust platform for guiding the morphogenesis and differentiation of fetal intestinal cells into mature engineered tissues that mimic their in vivo counterparts. Mechanistically, tissue maturation is driven by cell crowding, leading to reduced YAP1 activation. Modulating YAP signaling in both engineered tissues and the developing mouse intestine alters epithelial lineage specification. These findings uncover a geometry-dependent mechanism that links tissue architecture to cell fate transitions. Our work provides a platform for modeling aspects of intestinal development and offers insights for refining stem cell differentiation protocols and regenerative strategies for intestinal disorders.
    Keywords:  bioengineering; intestine; maturation; state transitions; stem cells
    DOI:  https://doi.org/10.1016/j.stem.2026.01.006
  5. Genes Dev. 2026 Feb 09.
    Metabolic permissiveness: how tissue context shapes cancer.
    Chrysanthi Moschandrea, Christian Frezza.
      An emerging paradox in cancer metabolism is that identical oncogenic mutations produce profoundly different metabolic phenotypes depending on tissue context, with many mutations exhibiting striking tissue-restricted distributions. Here we introduce metabolic permissiveness as the inherent capacity of a tissue to tolerate, adapt to, or exploit metabolic disruptions, providing a unifying framework for explaining this selectivity. We examine tissue-specific metabolic rewiring driven by canonical oncogenes (MYC and KRAS), tumor suppressors (p53, PTEN, and LKB1), and tricarboxylic acid (TCA) cycle enzymes (FH, SDH, and IDH), demonstrating that baseline metabolic architecture, nutrient microenvironment, redox buffering, and compensatory pathways determine whether mutations confer a selective advantage or metabolic crisis. We further discuss how the tumor microenvironment shapes metabolic adaptation and therapeutic vulnerability. This framework reveals shared principles of tissue-specific metabolic vulnerability in cancer and provides a mechanistic basis for precision metabolic therapies.
    Keywords:  cancer; metabolism; permissiveness
    DOI:  https://doi.org/10.1101/gad.353516.125
  6. Nat Rev Genet. 2026 Feb 10.
    Massively parallel reporter assays: from barcodes to biology.
    Fumitaka Inoue.
      
    DOI:  https://doi.org/10.1038/s41576-026-00944-4
  7. bioRxiv. 2026 Jan 26. pii: 2026.01.24.701406. [Epub ahead of print]
    Epithelial Reprogramming and Transition during Pulmonary Bioengineering.
    Satoshi Mizoguchi, Vi Lee, Hahram Kim, Sophie E Edelstein, Nuoya Wang, Maria Tomas Gracia, Colten Danelski, Connor Haynes, Rachel Rivero, David Stitelman, Tomohiro Obata, Allison M Greaney, Tomoshi Tsuchiya, Themis R Kyriakides, Naftali Kaminski, Micha Sam Brickman Raredon.
      Recent research has emphasized the critical role of cell state transitions in tissue homeostasis. In lung biology, transitional cells are recognized as a feature of tissue-scale processes during both normal physiology and disease. The precise way that transitional cell states emerge and are regulated remains to be determined. Engineered tissues, built in a laboratory through bioengineering approaches, allow detailed study of cellular states that are not commonly found in native biology, and allow opportunities to directly induce and manipulate cellular transitions. The following study explores and characterizes epithelial cell states that emerge via cellular reprogramming in a tissue engineering context.
    Abstract Figure:
    DOI:  https://doi.org/10.64898/2026.01.24.701406
  8. Nat Methods. 2026 Feb 10.
    Deep-coverage, high-throughput single-cell metabolomics.
      
    DOI:  https://doi.org/10.1038/s41592-025-02976-w
  9. STAR Protoc. 2026 Feb 11. pii: S2666-1667(26)00015-8. [Epub ahead of print]7(1): 104362
    Protocol for lentiviral engineering and multi-omic characterization of human kidney tubuloids.
    Giulia Perticari, Maroussia M P Ganpat, Jarno Drost.
      Organoids derived from normal human tissue have proven to be effective preclinical models for studying tumor progression through the introduction of driver mutations. In this protocol, we outline techniques for disease modeling using organoids derived from healthy kidney tissue, also known as tubuloids. We provide step-by-step instructions for the establishment and passaging of tubuloids, lentiviral transduction, processing for histological analysis, and preparation for CUT&RUN and single-cell transcriptomic profiling. For complete details on the use and execution of this protocol, please refer to Ganpat et al.1.
    Keywords:  Cancer; Cell Biology; Genomics; Organoids; Single Cell; Stem Cells
    DOI:  https://doi.org/10.1016/j.xpro.2026.104362
  10. bioRxiv. 2026 Feb 03. pii: 2026.01.31.702974. [Epub ahead of print]
    Epigenetic Gatekeeping of Intestinal Stem Cell Transformation.
    Alireza Lorzadeh, Sweta Sharma, Geroge Ye, Sabrina Rabaya, Yun Jee Kang, Ramesh A Shivdasani, Unmesh Jadhav.
      Widespread cell plasticity recognized in fetal intestinal epithelium is preserved in limited fashion in Wnt-responsive adult stem cells and contributes to tumor initiation, progression, and relapse. 1, 2, 3 It is unclear which epigenetic features maintain stem-cell properties, restrict adult expression of fetal genes 4 , and are attenuated in tumors, allowing non-stem cells to replenish targeted tumor stem cells 5 . Here we show that reversible stemness in normal adult intestinal crypt cells hinges on a dynamic balance between activating H3K27ac and repressive H3K27me3 marks. Cells that leave the Wnt-rich stem-cell niche normally acquire H3K27me3 at thousands of stemness-associated enhancers. Constitutive tumorigenic Wnt activity transforms Apc ‒/‒ intestinal stem cells by gradual erosion of H3K27me3 at select enhancers and extends stem-like properties beyond usual anatomic confines; continued depletion of H3K27me3 reactivates enhancers that control growth and expression of a wider swath of fetal genes than appreciated previously. Subsequent focal DNA demethylation at expanded superenhancer domains is associated with tumor growth. Human colorectal cancers also carry evidence of this epigenetic rewiring. Accelerated H3K27me3 loss in mice hastens, and its preservation delays, activation of stemness-related enhancers, superenhancers, and tumor progression. During transformation, H3K27me3 loss at enhancers erases a crucial distinction between stem and non-stem populations, endowing the latter with stemness and providing an explanation for tumor resistance to cancer stem cell targeting. Thus, H3K27me3 at Wnt-responsive enhancers is an intrinsic barrier to intestinal tumorigenesis and aberrant reactivation of hundreds of fetal genes.
    DOI:  https://doi.org/10.64898/2026.01.31.702974
  11. Front Bioinform. 2025 ;5 1715821
    Applications of AI to single-cell and spatial transcriptomics: current state-of-the-art and challenges.
    Boris Tchatchoua Ngassam, Huilin Niu, Sunny Pang, Valeryia Shydlouskaya, Tallulah S Andrews.
      Artificial intelligence (AI) has become a common tool for bioinformatics, with hundreds of methods published in recent years. Due to the training data demands of deep-learning algorithms, high-throughput single-cell and spatial transcriptomics is one of the most popular areas for these applications. Here we review how AI is being used for single-cell and spatial transcriptomics analysis, and how these approaches compare to alternative statistical or heuristic-based methods. We explored 10 common analysis tasks: dimensionality reduction, cross-dataset integration, data denoising, data augmentation, deconvolution, cell-cell interactions, transcriptional velocity, transcriptomic-chromatin accessibility integration, and integrating single-cell and spatial transcriptomics modalities. We highlight which algorithms are likely to be useful for discovery researchers, and which are not yet ready for general research use.
    Keywords:  cell-cell interactions; cross-dataset integration; data denoising; deconvolution; dimensionality reduction; integrating single-cell and spatial transcriptomics modalities; transcriptional velocity
    DOI:  https://doi.org/10.3389/fbinf.2025.1715821
  12. Cancer Discov. 2026 Feb 12. OF1
    AI Co-Scientists Move to the Front Lines of Cancer Research.
      Artificial intelligence systems are beginning to function as "co-scientists" in cancer research, generating drug candidates, prioritizing immunotherapy targets, and guiding experimental design. Emerging platforms now extend beyond analysis and hypothesis generation to participate directly in laboratory workflows, signaling a shift toward AI-augmented discovery across the oncology pipeline.
    DOI:  https://doi.org/10.1158/2159-8290.CD-NW2026-0015
  13. bioRxiv. 2026 Feb 02. pii: 2026.01.30.702946. [Epub ahead of print]
    Early microglial priming in Alzheimer's disease revealed by ME-seq.
    Bohan Zhu, Anurupa Ghosh, Zhe Wang, Zhicong Liao, Michael Appiah, Jiayi Li, Mimi Zhang, Federico Di Tullio, Agata Kurowski, John Fullard, Elvin Wagenblast, Martin J Walsh, Alison Goate, Panos Roussos, Ka Lung Cheung, Nan Yang, Sai Ma.
      Epigenetic modifications, particularly DNA methylation, change dynamically with aging and are implicated in Alzheimer's Disease (AD), yet how methylation interfaces with transcriptional and chromatin regulation at single-cell resolution remains poorly understood. Progress has been limited by a lack of scalable technologies capable of jointly profiling these regulatory layers. Here, we present ME-seq, a highly scalable technologies capable of simultaneously profiling DNA methylation, gene expression, and chromatin accessibility, while achieving a 100-fold reduction in cost. We generated over 400,000 single-nucleus trimodal profiles from the aging and AD mouse brain across ages, producing the first such atlas of neurodegeneration. We found AD progression triggers pronounced, disease-specific shifts in cellular composition, characterized by accelerated epigenetic aging and the expansion of disease-associated microglia (DAM). Integrative analyses, including aging clocks, revealed that DNA methylation acts as an early priming layer preceding transcriptional activation with IRF1 identified as a methylation-sensitive transcription factor serving as a gatekeeper for DAM activation. Our results establish ME-seq as a transformative tool for large-scale epigenomic dissection, revealing DNA methylation as a primary coordinator of cell-state transitions in the aging brain.
    Graphic abstract:
    DOI:  https://doi.org/10.64898/2026.01.30.702946
  14. Cell Res. 2026 Feb 09.
    Extrachromosomal DNA drives cancer evolution.
    Ilio Vitale, Alessandro D'Ambrosio, Lorenzo Galluzzi.
      
    DOI:  https://doi.org/10.1038/s41422-026-01225-9
  15. Bull Math Biol. 2026 Feb 09. 88(3): 36
    The Role of Fibroblast-Epithelial Cross-Talk on the Distribution of Distinct Fibroblast Phenotypes in the Intestinal Crypt.
    George Atkinson, Simon Leedham, Helen M Byrne.
      Intestinal crypts are test tube-like structures lined with an epithelial monolayer. Under homeostasis, mitotic forces drive epithelial cells to migrate up the crypt, from the stem cell niche. As the cells migrate up the crypt, they differentiate into specialised cells. This process is regulated by morphogen gradients established by distinct populations of subepithelial fibroblasts, and recent studies suggest fibroblasts and epithelial cells have co-evolved to maintain crypt structure and function via complementary morphogen expression. We present a mathematical model of fibroblast-epithelial cross-talk, in which fibroblast and epithelial phenotypes emerge from morphogen binding to cell surface receptors. The model predicts the formation of distinct zones of mutually supporting phenotypes at different crypt heights. These findings support the idea that fibroblast and epithelial cell phenotypes are an emergent property of the crypt microenvironment. We use the model to investigate how mutations in the fibroblasts may disrupt these phenotypic zones. Our results suggest that such mutations may lead to uncontrolled epithelial cell growth and, as such, indicate how dysfunctional fibroblasts may contribute to the emergence of colorectal cancer.
    Keywords:  BMP; BMPi; Cross-talk; Epithelial cells; Fibroblasts; Hedgehog; Intestinal crypts; Phenotype; WNT
    DOI:  https://doi.org/10.1007/s11538-025-01588-x
  16. bioRxiv. 2026 Feb 02. pii: 2026.02.02.703166. [Epub ahead of print]
    Single-Cell Atlas of Transcription and Chromatin States Reveals Regulatory Programs in the Human Brain.
    Yang Xie, Lei Chang, Guojie Zhong, Jonathan A Rink, Tatiana Báez-Becerra, Ethan Armand, Wubin Ding, Kai Li, Eric Bonne, Audrey Lie, Hannah S Indralingam, Keyi Dong, Timothy Loe, Bohan Huang, Zhaoning Wang, Ariana S Barcoma, Jackson K Willier, Kyle W Knutson, Jiayi Liu, Silvia Cho, Stella Cao, Kaitlyn G Russo, Carissa K Young, Jessica Arzavala, Yareli Sanchez, Aleksandra Bikkina, Natalie Schenker-Ahmed, Colin Kern, Zoey Zhao, Amit Klein, Jesus Flores, Chu-Yi Tai, Jacqueline Olness, Alexander Monell, Siavash Moghadami, Cesar Barragan, Chumo Chen, William Owens, Carolyn O'Connor, Michelle Liem, Mikayla V Marrin, Cynthia Rose, Shane N Alt, Nora Emerson, Julia Osteen, Jacinta Lucero, Daofeng Li, Rebecca D Hodge, Ting Wang, C Dirk Keene, Xiangming Xu, Quan Zhu, Joseph R Ecker, M Margarita Behrens, Bing Ren.
      Directly measuring chromatin states alongside transcription is essential for understanding how cell-type-specific regulatory programs are established and maintained in the adult human brain. We present a large-scale single-cell multimodal atlas generated by jointly profiling transcriptome with active (H3K27ac) and repressive (H3K27me3) histone modifications across 18 brain regions. We profile >750,000 nuclei spanning 160 cell types and integrate these data with chromatin accessibility, DNA methylation, 3D genome architecture, and spatial transcriptome. This framework annotates >500,000 regulatory elements and resolves cell-type-specific chromatin states. We link enhancers to target genes, infer gene regulatory networks, and classify chromatin interactions, revealing neuron-enriched long-range Polycomb repression of developmental genes. Integrating these maps with GWAS data and sequence-based model prioritizes noncoding variants, effector genes, and vulnerable cell types for neuropsychiatric disorders. Finally, cross-species comparisons show conserved activation but more divergent repression. Together, this study provides a functional reference for interpreting noncoding variants, epigenetic memory, and brain organization.
    HIGHLIGHTS: Joint single-cell profiling of transcriptomes with active or repressive histone modification in >750,000 nuclei across adult human brain. Chromatin state annotation of >500,000 candidate cis -regulatory elements distinguishes active enhancers from accessible and Polycomb-repressed regions. Cell-type-resolved regulatory networks and sequence-based deep learning model prioritize functional neuropsychiatric risk variants.Spatial epigenomic imputation reveals laminar layer-specific Polycomb repression programs.Integration with 3D genome architecture reveals neuron-specific super long-range chromatin loops silencing early developmental genes.Evolutionary analysis uncovers conserved active regulatory grammar but divergent repressive landscape.
    DOI:  https://doi.org/10.64898/2026.02.02.703166
  17. bioRxiv. 2026 Jan 30. pii: 2026.01.30.700779. [Epub ahead of print]
    Multiplexed enrichment and tracking of lineages with CloneSweeper.
    Robert J Vander Velde, Raymond W S Ng, Christopher Coté, Sydney M Shaffer.
      A fundamental challenge in studying therapy resistance is understanding whether it results from pre-existing cellular states ("priming") or drug-induced changes ("adaptation"). While lineage barcoding enables retrospective analysis of cells before and after treatment, current methods struggle to efficiently capture rare lineages in single-cell RNA sequencing (scRNA-seq) or isolate multiple specific lineages simultaneously for functional study. To overcome these limitations, we developed CloneSweeper, a multiplexed lineage tracking platform that pools enrichment libraries to isolate or enrich multiple rare lineages. CloneSweeper utilizes a dual-function barcode expressed as both a Cas9 gRNA for live-cell sorting and a 3' UTR transcript for high-recovery detection in 10x Genomics scRNA-seq. We applied CloneSweeper to a model of BRAF V600E melanoma, where we identified that resistance to targeted therapy emerges from a polyclonal population of rare, pre-existing lineages. By simultaneously targeting and enriching 21 distinct rare lineages prior to treatment, we defined a heritable, primed state characterized by de-differentiation and elevated mesenchymal markers. We demonstrate that these primed cells are not quiescent but instead exhibit upregulated inflammatory and stress response signaling, specifically via the AP-1 and NF-κB1 pathways. CloneSweeper thus provides a robust framework for dissecting the molecular mechanisms of rare biological phenomena through simultaneous, multiplexed lineage isolation.
    DOI:  https://doi.org/10.64898/2026.01.30.700779
This page is being maintained by Thomas Krichel. It was last updated on 2026‒03‒15 at 19:10.