bims-gerecp Biomed News
on Gene regulatory networks of epithelial cell plasticity
Issue of 2024–08–18
eleven papers selected by
Xiao Qin, University of Oxford
  1. Associating transcription factors to single-cell trajectories with DREAMIT.
  2. Transformers in single-cell omics: a review and new perspectives.
  3. Combinatorial regulatory states define cell fate diversity during embryogenesis.
  4. Integrative single-cell analysis of human colorectal cancer reveals patient stratification with distinct immune evasion mechanisms.
  5. EPInformer: a scalable deep learning framework for gene expression prediction by integrating promoter-enhancer sequences with multimodal epigenomic data.
  6. Global transcription regulation revealed from dynamical correlations in time-resolved single-cell RNA sequencing.
  7. An In Vivo Metastasis Model Using Genotype-Defined Tumor Organoids.
  8. Comprehensive transcription factor perturbations recapitulate fibroblast transcriptional states.
  9. Precision epigenetic editing: Technological advances, enduring challenges, and therapeutic applications.
  10. From single cell to spatial multi-omics: unveiling molecular mechanisms in dynamic and heterogeneous systems.
  11. Human organoids with an autologous tissue-resident immune compartment.
  1. Genome Biol. 2024 Aug 14. 25(1): 220
    Associating transcription factors to single-cell trajectories with DREAMIT.
    Nathan D Maulding, Lucas Seninge, Joshua M Stuart.
      Inferring gene regulatory networks from single-cell RNA-sequencing trajectories has been an active area of research yet methods are still needed to identify regulators governing cell transitions. We developed DREAMIT (Dynamic Regulation of Expression Across Modules in Inferred Trajectories) to annotate transcription-factor activity along single-cell trajectory branches, using ensembles of relations to target genes. Using a benchmark representing several different tissues, as well as external validation with ATAC-Seq and Perturb-Seq data on hematopoietic cells, the method was found to have higher tissue-specific sensitivity and specificity over competing approaches.
    DOI:  https://doi.org/10.1186/s13059-024-03368-7
  2. Nat Methods. 2024 Aug;21(8): 1430-1443
    Transformers in single-cell omics: a review and new perspectives.
    Artur Szałata, Karin Hrovatin, Sören Becker, Alejandro Tejada-Lapuerta, Haotian Cui, Bo Wang, Fabian J Theis.
      Recent efforts to construct reference maps of cellular phenotypes have expanded the volume and diversity of single-cell omics data, providing an unprecedented resource for studying cell properties. Despite the availability of rich datasets and their continued growth, current single-cell models are unable to fully capitalize on the information they contain. Transformers have become the architecture of choice for foundation models in other domains owing to their ability to generalize to heterogeneous, large-scale datasets. Thus, the question arises of whether transformers could set off a similar shift in the field of single-cell modeling. Here we first describe the transformer architecture and its single-cell adaptations and then present a comprehensive review of the existing applications of transformers in single-cell analysis and critically discuss their future potential for single-cell biology. By studying limitations and technical challenges, we aim to provide a structured outlook for future research directions at the intersection of machine learning and single-cell biology.
    DOI:  https://doi.org/10.1038/s41592-024-02353-z
  3. Nat Commun. 2024 Aug 09. 15(1): 6841
    Combinatorial regulatory states define cell fate diversity during embryogenesis.
    Jonathan E Valencia, Isabelle S Peter.
      Cell fate specification occurs along invariant species-specific trajectories that define the animal body plan. This process is controlled by gene regulatory networks that regulate the expression of the limited set of transcription factors encoded in animal genomes. Here we globally assess the spatial expression of ~90% of expressed transcription factors during sea urchin development from embryo to larva to determine the activity of gene regulatory networks and their regulatory states during cell fate specification. We show that >200 embryonically expressed transcription factors together define >70 cell fates that recapitulate the morphological and functional organization of this organism. Most cell fate-specific regulatory states consist of ~15-40 transcription factors with similarity particularly among functionally related cell types regardless of developmental origin. Temporally, regulatory states change continuously during development, indicating that progressive changes in regulatory circuit activity determine cell fate specification. We conclude that the combinatorial expression of transcription factors provides molecular definitions that suffice for the unique specification of cell states in time and space during embryogenesis.
    DOI:  https://doi.org/10.1038/s41467-024-50822-y
  4. Nat Cancer. 2024 Aug 15.
    Integrative single-cell analysis of human colorectal cancer reveals patient stratification with distinct immune evasion mechanisms.
    Xiaojing Chu, Xiangjie Li, Yu Zhang, Guohui Dang, Yuhui Miao, Wenbin Xu, Jinyu Wang, Zemin Zhang, Sijin Cheng.
      The tumor microenvironment (TME) considerably influences colorectal cancer (CRC) progression, therapeutic response and clinical outcome, but studies of interindividual heterogeneities of the TME in CRC are lacking. Here, by integrating human colorectal single-cell transcriptomic data from approximately 200 donors, we comprehensively characterized transcriptional remodeling in the TME compared to noncancer tissues and identified a rare tumor-specific subset of endothelial cells with T cell recruitment potential. The large sample size enabled us to stratify patients based on their TME heterogeneity, revealing divergent TME subtypes in which cancer cells exploit different immune evasion mechanisms. Additionally, by associating single-cell transcriptional profiling with risk genes identified by genome-wide association studies, we determined that stromal cells are major effector cell types in CRC genetic susceptibility. In summary, our results provide valuable insights into CRC pathogenesis and might help with the development of personalized immune therapies.
    DOI:  https://doi.org/10.1038/s43018-024-00807-z
  5. bioRxiv. 2024 Aug 01. pii: 2024.08.01.606099. [Epub ahead of print]
    EPInformer: a scalable deep learning framework for gene expression prediction by integrating promoter-enhancer sequences with multimodal epigenomic data.
    Jiecong Lin, Ruibang Luo, Luca Pinello.
      Transcriptional regulation, critical for cellular differentiation and adaptation to environmental changes, involves coordinated interactions among DNA sequences, regulatory proteins, and chromatin architecture. Despite extensive data from consortia like ENCODE, understanding the dynamics of cis-regulatory elements (CREs) in gene expression remains challenging. Deep learning is a powerful tool for learning gene expression and epigenomic signals from DNA sequences, exhibiting superior performance compared to conventional machine learning approaches. However, even the most advanced deep learning-based methods may fall short in capturing the regulatory effects of distal elements such as enhancers, limiting their predictive accuracy. In addition, these methods may require significant resources to train or to adapt to newly generated data. To address these challenges, we present EPInformer, a scalable deep-learning framework for predicting gene expression by integrating promoter-enhancer interactions with their sequences, epigenomic signals, and chromatin contacts. Our model outperforms existing gene expression prediction models in rigorous cross-chromosome validation, accurately recapitulates enhancer-gene interactions validated by CRISPR perturbation experiments, and identifies crucial transcription factor motifs within regulatory sequences. EPInformer is available as open-source software at https://github.com/pinellolab/EPInformer.
    DOI:  https://doi.org/10.1101/2024.08.01.606099
  6. Cell Syst. 2024 Aug 01. pii: S2405-4712(24)00201-1. [Epub ahead of print]
    Global transcription regulation revealed from dynamical correlations in time-resolved single-cell RNA sequencing.
    Dimitris Volteras, Vahid Shahrezaei, Philipp Thomas.
      Single-cell transcriptomics reveals significant variations in transcriptional activity across cells. Yet, it remains challenging to identify mechanisms of transcription dynamics from static snapshots. It is thus still unknown what drives global transcription dynamics in single cells. We present a stochastic model of gene expression with cell size- and cell cycle-dependent rates in growing and dividing cells that harnesses temporal dimensions of single-cell RNA sequencing through metabolic labeling protocols and cel lcycle reporters. We develop a parallel and highly scalable approximate Bayesian computation method that corrects for technical variation and accurately quantifies absolute burst frequency, burst size, and degradation rate along the cell cycle at a transcriptome-wide scale. Using Bayesian model selection, we reveal scaling between transcription rates and cell size and unveil waves of gene regulation across the cell cycle-dependent transcriptome. Our study shows that stochastic modeling of dynamical correlations identifies global mechanisms of transcription regulation. A record of this paper's transparent peer review process is included in the supplemental information.
    Keywords:  approximate Bayesian computation; cell cycle; gene expression noise; genomics; modeling; single-cell transcriptomics; statistical inference; time-resolved; transcription dynamics; transcriptional bursting
    DOI:  https://doi.org/10.1016/j.cels.2024.07.002
  7. Methods Mol Biol. 2024 ;2828 57-68
    An In Vivo Metastasis Model Using Genotype-Defined Tumor Organoids.
    Atsuya Morita, Mizuho Nakayama, Hiroko Oshima, Masanobu Oshima.
      Recent cancer genome analyses have identified frequently mutated genes that are responsible for the development and malignant progression of cancers, including colorectal cancer (CRC). We previously constructed mouse models that carried major driver mutations of CRC, namely Apc, Kras, Tgfbr2, Trp53, and Fbxw7, in combinations. Comprehensive histological analyses of the models showed a link between mutation combinations and malignant phenotypes, such as invasion, epithelial-mesenchymal transition (EMT), and metastasis. The major cause of cancer-related death is metastasis, making it important to understand the mechanism underlying metastasis in order to develop novel therapeutic strategies. To this end, we have established intestinal tumor-derived organoids from different genotyped mice and generated liver metastasis models via transplantation of the organoids into the spleen. Through histological and imaging analyses of the transplantation models, we have determined that the combination of Apc, Kras, Tgfbr2, and Trp53 mutations promotes liver metastasis at a high incidence. We also demonstrated polyclonal metastasis of tumor cell clusters consisting of genetically and phenotypically distinct cells through our model analysis. These organoid transplantation models recapitulate human CRC metastasis, constituting a useful tool for basic and clinical cancer research as a preclinical model. We herein report the experimental protocols of the organoid culture and generation of metastasis models.
    Keywords:  Colon cancer; Imaging; Liver metastasis; Mouse models; Organoids
    DOI:  https://doi.org/10.1007/978-1-0716-4023-4_6
  8. bioRxiv. 2024 Aug 03. pii: 2024.07.31.606073. [Epub ahead of print]
    Comprehensive transcription factor perturbations recapitulate fibroblast transcriptional states.
    Kaden M Southard, Rico C Ardy, Anran Tang, Deirdre D O'Sullivan, Eli Metzner, Karthik Guruvayurappan, Thomas M Norman.
      Cell atlas projects have nominated recurrent transcriptional states as drivers of biological processes and disease, but their origins, regulation, and properties remain unclear. To enable complementary functional studies, we developed a scalable approach for recapitulating cell states in vitro using CRISPR activation (CRISPRa) Perturb-seq. Aided by a novel multiplexing method, we activated 1,836 transcription factors in two cell types. Measuring 21,958 perturbations showed that CRISPRa activated targets within physiological ranges, that epigenetic features predicted activatable genes, and that the protospacer seed region drove an off-target effect. Perturbations recapitulated in vivo fibroblast states, including universal and inflammatory states, and identified KLF4 and KLF5 as key regulators of the universal state. Inducing the universal state suppressed disease-associated states, highlighting its therapeutic potential. Our findings cement CRISPRa as a tool for perturbing differentiated cells and indicate that in vivo states can be elicited via perturbation, enabling studies of clinically relevant states ex vivo .
    DOI:  https://doi.org/10.1101/2024.07.31.606073
  9. Cell Chem Biol. 2024 Aug 06. pii: S2451-9456(24)00309-X. [Epub ahead of print]
    Precision epigenetic editing: Technological advances, enduring challenges, and therapeutic applications.
    Goldie V Roth, Isabella R Gengaro, Lei S Qi.
      The epigenome is a complex framework through which gene expression is precisely and flexibly modulated to incorporate heritable memory and responses to environmental stimuli. It governs diverse cellular processes, including cell fate, disease, and aging. The need to understand this system and precisely control gene expression outputs for therapeutic purposes has precipitated the development of a diverse set of epigenetic editing tools. Here, we review the existing toolbox for targeted epigenetic editing, technical considerations of the current technologies, and opportunities for future development. We describe applications of therapeutic epigenetic editing and their potential for treating disease, with a discussion of ongoing delivery challenges that impede certain clinical interventions, particularly in the brain. With simultaneous advancements in available engineering tools and appropriate delivery technologies, we predict that epigenetic editing will increasingly cement itself as a powerful approach for safely treating a wide range of disorders in all tissues of the body.
    Keywords:  CRISPR; chromatin modifications; chromatin reorganization; delivery; epigenetic disease; epigenetic editing; epigenetics; epigenome therapy; neurological disease
    DOI:  https://doi.org/10.1016/j.chembiol.2024.07.007
  10. Curr Opin Biotechnol. 2024 Aug 08. pii: S0958-1669(24)00110-1. [Epub ahead of print]89 103174
    From single cell to spatial multi-omics: unveiling molecular mechanisms in dynamic and heterogeneous systems.
    Ruonan Wu, Marija Veličković, Kristin E Burnum-Johnson.
      Single-cell multi-omics and spatial technology have been widely applied to biomedical studies and recently to environmental studies. The cell size detected by single-cell omics ranges from ∼2 µm (e.g., Bacillus subtilis) to ∼120 µm (e.g., human oocytes). Simultaneous detection of single-cell multi-omics is available to human and plant tissues while limited to microbial samples. Spatial technology enables mapping the detected biomolecules in situ. The recent advances in Matrix-Assisted Laser Desorption/Ionization-Mass Spectrometry Imaging and Micro/Nanodroplet Processing in One Pot for Trace Samples for the first time allow the application of spatial multi-omics in highly heterogeneous environmental samples composed of plants, fungi, and bacteria. We envision that these technologies will continue to advance our understanding of unique cell types, their developmental trajectory, and the intercellular signaling and interaction within biological samples.
    DOI:  https://doi.org/10.1016/j.copbio.2024.103174
  11. Nature. 2024 Aug 14.
    Human organoids with an autologous tissue-resident immune compartment.
    Timothy Recaldin, Linda Steinacher, Bruno Gjeta, Marius F Harter, Lukas Adam, Kristina Kromer, Marisa Pimentel Mendes, Marina Bellavista, Mikhail Nikolaev, Giacomo Lazzaroni, Rok Krese, Umut Kilik, Doris Popovic, Bilgenaz Stoll, Régine Gerard, Michael Bscheider, Marc Bickle, Lauriane Cabon, J Gray Camp, Nikolche Gjorevski.
      The intimate relationship between the epithelium and immune system is crucial for maintaining tissue homeostasis, with perturbations therein linked to autoimmune disease and cancer1-3. Whereas stem cell-derived organoids are powerful models of epithelial function4, they lack tissue-resident immune cells that are essential for capturing organ-level processes. We describe human intestinal immuno-organoids (IIOs), formed through self-organization of epithelial organoids and autologous tissue-resident memory T (TRM) cells, a portion of which integrate within the epithelium and continuously survey the barrier. TRM cell migration and interaction with epithelial cells was orchestrated by TRM cell-enriched transcriptomic programs governing cell motility and adhesion. We combined IIOs and single-cell transcriptomics to investigate intestinal inflammation triggered by cancer-targeting biologics in patients. Inflammation was associated with the emergence of an activated population of CD8+ T cells that progressively acquired intraepithelial and cytotoxic features. The appearance of this effector population was preceded and potentiated by a T helper-1-like CD4+ population, which initially produced cytokines and subsequently became cytotoxic itself. As a system amenable to direct perturbation, IIOs allowed us to identify the Rho pathway as a new target for mitigation of immunotherapy-associated intestinal inflammation. Given that they recapitulate both the phenotypic outcomes and underlying interlineage immune interactions, IIOs can be used to study tissue-resident immune responses in the context of tumorigenesis and infectious and autoimmune diseases.
    DOI:  https://doi.org/10.1038/s41586-024-07791-5
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