bims-gerecp Biomed News
on Gene regulatory networks of epithelial cell plasticity
Issue of 2025–03–30
twelve papers selected by
Xiao Qin, University of Oxford
  1. DARLIN mouse for in vivo lineage tracing at high efficiency and clonal diversity.
  2. CellPhoneDB v5: inferring cell-cell communication from single-cell multiomics data.
  3. Time, the final frontier.
  4. Advancing cell-cell communication analysis from single-cell genomics data.
  5. Tackling the next decade of cancer research.
  6. Harnessing the Power of Metabolomics for Precision Oncology: Current Advances and Future Directions.
  7. Spatially resolved genome-wide joint profiling of epigenome and transcriptome with spatial-ATAC-RNA-seq and spatial-CUT&Tag-RNA-seq.
  8. CT Colonography for Colorectal Cancer Screening: Challenges and Opportunities for Clinical Integration.
  9. In vivo targeted and deterministic single-cell malignant transformation.
  10. Chromatin accessibility landscape of mouse early embryos revealed by single-cell NanoATAC-seq2.
  11. Identification of a SNAI1 enhancer RNA that drives cancer cell plasticity.
  12. High-throughput screening of human genetic variants by pooled prime editing.
  1. Nat Protoc. 2025 Mar 21.
    DARLIN mouse for in vivo lineage tracing at high efficiency and clonal diversity.
    Li Li, Sarah Bowling, Hongying Lin, Daolong Chen, Shou-Wen Wang, Fernando D Camargo.
      Lineage tracing is a powerful tool to study cell history and cell dynamics during tissue development and homeostasis. An increasingly popular approach for lineage tracing is to generate high-frequent mutations at given genomic loci, which can serve as genetic barcodes to label different cell lineages. However, current lineage tracing mouse models suffer from low barcode diversity and limited single-cell lineage coverage. We recently developed the DARLIN mouse model by incorporating three barcoding arrays within defined genomic loci and combining Cas9 and terminal deoxynucleotidyl transferase (TdT) to improve editing diversity in each barcode array. We estimated that DARLIN generates 1018 distinct lineage barcodes in theory, and enables the recovery of lineage barcodes in over 70% of cells in single-cell assays. In addition, DARLIN can be induced with doxycycline to generate stable lineage barcodes across different tissues at a defined stage. Here we provide a step-by-step protocol on applying the DARLIN system for in vivo lineage tracing, including barcode induction, estimation of induction efficiency, barcode analysis with bulk and single-cell sequencing, and computational analysis. The execution time of this protocol is ~1 week for experimental data collection and ~1 d for running the computational analysis pipeline. To execute this protocol, one should be familiar with sequencing library generation and Linux operation. DARLIN opens the door to study the lineage relationships and the underlying molecular regulations across various tissues at physiological context.
    DOI:  https://doi.org/10.1038/s41596-025-01141-z
  2. Nat Protoc. 2025 Mar 25.
    CellPhoneDB v5: inferring cell-cell communication from single-cell multiomics data.
    Kevin Troulé, Robert Petryszak, Batuhan Cakir, James Cranley, Alicia Harasty, Martin Prete, Zewen Kelvin Tuong, Sarah A Teichmann, Luz Garcia-Alonso, Roser Vento-Tormo.
      Cell-cell communication is essential for tissue development, function and regeneration. The revolution of single-cell genomics technologies offers an unprecedented opportunity to uncover how cells communicate in vivo within their tissue niches and how disruption of these niches can lead to diseases and developmental abnormalities. CellPhoneDB is a bioinformatics toolkit designed to infer cell-cell communication by combining a curated repository of bona fide ligand-receptor interactions with methods to integrate these interactions with single-cell genomics data. Here we present a protocol for the latest version of CellPhoneDB (v5), offering several new features. First, the repository has been expanded by one-third with the addition of new interactions, including ~1,000 interactions mediated by nonpeptidic ligands such as steroidogenic hormones, neurotransmitters and small G-protein-coupled receptor (GPCR)-binding ligands. Second, we outline a new way of using the database that allows users to tailor queries to their experimental designs. Third, the update incorporates novel strategies to prioritize specific cell-cell interactions, leveraging information from other modalities such as tissue microenvironments derived from spatial transcriptomics technologies or transcription factor activities derived from a single-cell assay for transposase accessible chromatin assays. Finally, we describe the new CellPhoneDBViz module to interactively visualize and share results. Altogether, CellPhoneDB v5 enhances the precision of cell-cell communication inference, offering new insights into tissue biology in physiological microenvironments. This protocol typically takes ~15 min and requires basic knowledge of python.
    DOI:  https://doi.org/10.1038/s41596-024-01137-1
  3. Mol Oncol. 2025 Mar 24.
    Time, the final frontier.
    Gautier Follain, Michal Dibus, Omkar Joshi, Guillaume Jacquemet.
      Cancer's notorious heterogeneity poses significant challenges, as each tumor comprises a unique ecosystem. While single-cell and spatial transcriptomics advancements have transformed our understanding of spatial diversity within tumors, the temporal dimension remains underexplored. Tumors are dynamic entities that continuously evolve and adapt, and relying solely on static snapshots obscures the intricate interplay between cancer cells and their microenvironment. Here, we advocate for integrating temporal dynamics into cancer research, emphasizing a fundamental shift from traditional endpoint experiments to data-driven, continuous approaches. This integration involves, for instance, the development of advanced live imaging techniques, innovative temporal omics methodologies, and novel computational tools.
    Keywords:  cancer heterogeneity; circadian clock; live‐cell imaging; metastasis; temporal dynamics; temporal omics
    DOI:  https://doi.org/10.1002/1878-0261.70025
  4. Nat Protoc. 2025 Mar 25.
    Advancing cell-cell communication analysis from single-cell genomics data.
    Iguaracy Pinheiro-de-Sousa, Evangelia Petsalaki.
      
    DOI:  https://doi.org/10.1038/s41596-025-01140-0
  5. Trends Cancer. 2025 Mar 24. pii: S2405-8033(25)00072-X. [Epub ahead of print]
    Tackling the next decade of cancer research.
    Raza Ali, Brittany Jenkins, Wouter Karthaus, Jana Lipkova, Sandra Misale, Jens Puschhof, Melody Smith, Santosha Vardhana, Xin Zhou.
      
    DOI:  https://doi.org/10.1016/j.trecan.2025.03.004
  6. Cells. 2025 Mar 10. pii: 402. [Epub ahead of print]14(6):
    Harnessing the Power of Metabolomics for Precision Oncology: Current Advances and Future Directions.
    Manas Kohli, George Poulogiannis.
      Metabolic reprogramming is a hallmark of cancer, with cancer cells acquiring many unique metabolic traits to support malignant growth, and extensive intra- and inter-tumour metabolic heterogeneity. Understanding these metabolic characteristics presents opportunities in precision medicine for both diagnosis and therapy. However, despite its potential, metabolic phenotyping has lagged behind genetic, transcriptomic, and immunohistochemical profiling in clinical applications. This is partly due to the lack of a single experimental technique capable of profiling the entire metabolome, necessitating the use of multiple technologies and approaches to capture the full range of cancer metabolic plasticity. This review examines the repertoire of tools available for profiling cancer metabolism, demonstrating their applications in preclinical and clinical settings. It also presents case studies illustrating how metabolomic profiling has been integrated with other omics technologies to gain insights into tumour biology and guide treatment strategies. This information aims to assist researchers in selecting the most effective tools for their studies and highlights the importance of combining different metabolic profiling techniques to comprehensively understand tumour metabolism.
    Keywords:  cancer; metabolome; metabolomics; precision medicine; therapy
    DOI:  https://doi.org/10.3390/cells14060402
  7. Nat Protoc. 2025 Mar 21.
    Spatially resolved genome-wide joint profiling of epigenome and transcriptome with spatial-ATAC-RNA-seq and spatial-CUT&Tag-RNA-seq.
    Haikuo Li, Shuozhen Bao, Negin Farzad, Xiaoyu Qin, Anthony A Fung, Di Zhang, Zhiliang Bai, Bo Tao, Rong Fan.
      The epigenome of a cell is tightly correlated with gene transcription, which controls cell identity and diverse biological activities. Recent advances in spatial technologies have improved our understanding of tissue heterogeneity by analyzing transcriptomics or epigenomics with spatial information preserved, but have been mainly restricted to one molecular layer at a time. Here we present procedures for two spatially resolved sequencing methods, spatial-ATAC-RNA-seq and spatial-CUT&Tag-RNA-seq, that co-profile transcriptome and epigenome genome wide. In both methods, transcriptomic readouts are generated through tissue fixation, permeabilization and in situ reverse transcription. In spatial-ATAC-RNA-seq, Tn5 transposase is used to probe accessible chromatin, and in spatial-CUT&Tag-RNA-seq, the tissue is incubated with primary antibodies that target histone modifications, followed by Protein A-fused Tn5-induced tagmentation. Both methods leverage a microfluidic device that delivers two sets of oligonucleotide barcodes to generate a two-dimensional mosaic of tissue pixels at near single-cell resolution. A spatial-ATAC-RNA-seq or spatial-CUT&Tag-RNA-seq library can be generated in 3-5 d, allowing researchers to simultaneously investigate the transcriptomic landscape and epigenomic landscape of an intact tissue section. This protocol is an extension of our previous spatially resolved epigenome sequencing protocol and provides opportunities in multimodal profiling.
    DOI:  https://doi.org/10.1038/s41596-025-01145-9
  8. AJR Am J Roentgenol. 2025 Mar 26.
    CT Colonography for Colorectal Cancer Screening: Challenges and Opportunities for Clinical Integration.
    Francesca Castagnoli.
      
    DOI:  https://doi.org/10.2214/AJR.25.32963
  9. Elife. 2025 Mar 25. pii: RP97650. [Epub ahead of print]13
    In vivo targeted and deterministic single-cell malignant transformation.
    Pierluigi Scerbo, Benjamin Tisserand, Marine Delagrange, Héloise Debare, David Bensimon, Bertrand Ducos.
      Why does a normal cell possibly harboring genetic mutations in oncogene or tumor suppressor genes becomes malignant and develops a tumor is a subject of intense debate. Various theories have been proposed but their experimental test has been hampered by the unpredictable and improbable malignant transformation of single cells. Here, using an optogenetic approach we permanently turn on an oncogene (KRASG12V) in a single cell of a zebrafish brain that, only in synergy with the transient co-activation of a reprogramming factor (VENTX/NANOG/OCT4), undergoes a deterministic malignant transition and robustly and reproducibly develops within 6 days into a full-blown tumor. The controlled way in which a single cell can thus be manipulated to give rise to cancer lends support to the 'ground state theory of cancer initiation' through 'short-range dispersal' of the first malignant cells preceding tumor growth.
    Keywords:  Danio rerio; cancer; cancer biology; optogenetics; zebrafish
    DOI:  https://doi.org/10.7554/eLife.97650
  10. Science. 2025 Mar 28. 387(6741): eadp4319
    Chromatin accessibility landscape of mouse early embryos revealed by single-cell NanoATAC-seq2.
    Mengyao Li, Zhenhuan Jiang, Xueqiang Xu, Xinglong Wu, Yun Liu, Kexuan Chen, Yuhan Liao, Wen Li, Xiao Wang, Yuqing Guo, Bo Zhang, Lu Wen, Kehkooi Kee, Fuchou Tang.
      In mammals, fertilized eggs undergo genome-wide epigenetic reprogramming to generate the organism. However, our understanding of epigenetic dynamics during preimplantation development at single-cell resolution remains incomplete. Here, we developed scNanoATAC-seq2, a single-cell assay for transposase-accessible chromatin using long-read sequencing for scarce samples. We present a detailed chromatin accessibility landscape of mouse preimplantation development, revealing distinct chromatin signatures in the epiblast, primitive endoderm, and trophectoderm during lineage segregation. Differences between zygotes and two-cell embryos highlight reprogramming in chromatin accessibility during the maternal-to-zygotic transition. Single-cell long-read sequencing enables in-depth analysis of chromatin accessibility in noncanonical imprinting, imprinted X chromosome inactivation, and low-mappability genomic regions, such as repetitive elements and paralogs. Our data provide insights into chromatin dynamics during mammalian preimplantation development and lineage differentiation.
    DOI:  https://doi.org/10.1126/science.adp4319
  11. Nat Commun. 2025 Mar 25. 16(1): 2890
    Identification of a SNAI1 enhancer RNA that drives cancer cell plasticity.
    Chuannan Fan, Qian Wang, Peter H L Krijger, Davy Cats, Miriam Selle, Olga Khorosjutina, Soniya Dhanjal, Bernhard Schmierer, Hailiang Mei, Wouter de Laat, Peter Ten Dijke.
      Enhancer RNAs (eRNAs) are a pivotal class of enhancer-derived non-coding RNAs that drive gene expression. Here we identify the SNAI1 enhancer RNA (SNAI1e; SCREEM2) as a key activator of SNAI1 expression and a potent enforcer of transforming growth factor-β (TGF-β)/SMAD signaling in cancer cells. SNAI1e depletion impairs TGF-β-induced epithelial-mesenchymal transition (EMT), migration, in vivo extravasation, stemness, and chemotherapy resistance in breast cancer cells. SNAI1e functions as an eRNA to cis-regulate SNAI1 enhancer activity by binding to and strengthening the enrichment of the transcriptional co-activator bromodomain containing protein 4 (BRD4) at the local enhancer. SNAI1e selectively promotes the expression of SNAI1, which encodes the EMT transcription factor SNAI1. Furthermore, we reveal that SNAI1 interacts with and anchors the inhibitory SMAD7 in the nucleus, and thereby prevents TGF-β type I receptor (TβRI) polyubiquitination and proteasomal degradation. Our findings establish SNAI1e as a critical driver of SNAI1 expression and TGF-β-induced cell plasticity.
    DOI:  https://doi.org/10.1038/s41467-025-58032-w
  12. Cell Genom. 2025 Mar 18. pii: S2666-979X(25)00070-9. [Epub ahead of print] 100814
    High-throughput screening of human genetic variants by pooled prime editing.
    Michael Herger, Christina M Kajba, Megan Buckley, Ana Cunha, Molly Strom, Gregory M Findlay.
      Multiplexed assays of variant effect (MAVEs) enable scalable functional assessment of human genetic variants. However, established MAVEs are limited by exogenous expression of variants or constraints of genome editing. Here, we introduce a pooled prime editing (PE) platform to scalably assay variants in their endogenous context. We first improve efficiency of PE in HAP1 cells, defining optimal prime editing guide RNA (pegRNA) designs and establishing enrichment of edited cells via co-selection. We next demonstrate negative selection screening by testing over 7,500 pegRNAs targeting SMARCB1 and observing depletion of efficiently installed loss-of-function (LoF) variants. We then screen for LoF variants in MLH1 via 6-thioguanine selection, testing 65.3% of all possible SNVs in a 200-bp region including exon 10 and 362 non-coding variants from ClinVar spanning a 60-kb region. The platform's overall accuracy for discriminating pathogenic variants indicates that it will be highly valuable for identifying new variants underlying diverse human phenotypes across large genomic regions.
    Keywords:  MAVE; MLH1; PE; SMARCB1; functional genomics; genome-editing technology; multiplexed assay of variant effect; precision medicine; prime editing; saturation mutagenesis
    DOI:  https://doi.org/10.1016/j.xgen.2025.100814
This page is being maintained by Thomas Krichel. It was last updated on 2025‒04‒08 at 7:38.