bims-gerecp Biomed News
on Gene regulatory networks of epithelial cell plasticity
Issue of 2024–11–24
twenty-one papers selected by
Xiao Qin, University of Oxford



  1. Genome Res. 2024 Nov 21.
      Single-cell lineage tracing (scLT) has emerged as a powerful tool, providing unparalleled resolution to investigate cellular dynamics, fate determination, and the underlying molecular mechanisms. This review thoroughly examines the latest prospective lineage DNA barcode tracing technologies. It further highlights pivotal studies that leverage single-cell lentiviral integration barcoding technology to unravel the dynamic nature of cell lineages in both developmental biology and cancer research. Additionally, the review navigates through critical considerations for successful experimental design in lineage tracing and addresses challenges inherent in this field, including technical limitations, complexities in data analysis, and the imperative for standardization. It also outlines current gaps in knowledge and suggests future research directions, contributing to the ongoing advancement of scLT studies.
    DOI:  https://doi.org/10.1101/gr.278944.124
  2. Nature. 2024 Nov;635(8039): 690-698
    Human Cell Atlas Organoid Biological Network
      Human neural organoids, generated from pluripotent stem cells in vitro, are useful tools to study human brain development, evolution and disease. However, it is unclear which parts of the human brain are covered by existing protocols, and it has been difficult to quantitatively assess organoid variation and fidelity. Here we integrate 36 single-cell transcriptomic datasets spanning 26 protocols into one integrated human neural organoid cell atlas totalling more than 1.7 million cells1-26. Mapping to developing human brain references27-30 shows primary cell types and states that have been generated in vitro, and estimates transcriptomic similarity between primary and organoid counterparts across protocols. We provide a programmatic interface to browse the atlas and query new datasets, and showcase the power of the atlas to annotate organoid cell types and evaluate new organoid protocols. Finally, we show that the atlas can be used as a diverse control cohort to annotate and compare organoid models of neural disease, identifying genes and pathways that may underlie pathological mechanisms with the neural models. The human neural organoid cell atlas will be useful to assess organoid fidelity, characterize perturbed and diseased states and facilitate protocol development.
    DOI:  https://doi.org/10.1038/s41586-024-08172-8
  3. Nat Biotechnol. 2024 Nov 21.
      Pooled single-cell CRISPR screens have profiled either gene expression or chromatin accessibility but not both modalities. Here we develop MultiPerturb-seq, a high-throughput CRISPR screening platform with joint single-nucleus chromatin accessibility, transcriptome and guide RNA capture using combinatorial indexing combined with droplet microfluidics to scale throughput and integrate all three modalities. We identify key differentiation genes in a rare pediatric cancer and establish ZNHIT1 as a potential target for cancer reprogramming therapy.
    DOI:  https://doi.org/10.1038/s41587-024-02475-x
  4. Immunotherapy. 2024 Nov 16. 1-3
      
    Keywords:  Colorectal; cancer immunology; checkpoint inhibitors; colon; fruquintinib; immunotherapy; tyrosine kinase inhibitors
    DOI:  https://doi.org/10.1080/1750743X.2024.2430173
  5. Nature. 2024 Nov 20.
      The intestine is characterized by an environment in which host requirements for nutrient and water absorption are consequently paired with the requirements to establish tolerance to the outside environment. To better understand how the intestine functions in health and disease, large efforts have been made to characterize the identity and composition of cells from different intestinal regions1-8. However, the robustness, nature of adaptability and extent of resilience of the transcriptional landscape and cellular underpinning of the intestine in space are still poorly understood. Here we generated an integrated resource of the spatial and cellular landscape of the murine intestine in the steady and perturbed states. Leveraging these data, we demonstrated that the spatial landscape of the intestine was robust to the influence of the microbiota and was adaptable in a spatially restricted manner. Deploying a model of spatiotemporal acute inflammation, we demonstrated that both robust and adaptable features of the landscape were resilient. Moreover, highlighting the physiological relevance and value of our dataset, we identified a region of the middle colon characterized by an immune-driven multicellular spatial adaptation of structural cells to the microbiota. Our results demonstrate that intestinal regionalization is characterized by robust and resilient structural cell states and that the intestine can adapt to environmental stress in a spatially controlled manner through the crosstalk between immunity and structural cell homeostasis.
    DOI:  https://doi.org/10.1038/s41586-024-08216-z
  6. Development. 2024 Nov 22. pii: dev.203102. [Epub ahead of print]
      Developmental signaling inputs are fundamental for shaping cell fates and behavior. However, traditional fluorescent-based signaling reporters have limitations in scalability and molecular resolution of cell types. We present SABER-seq, a CRISPR-Cas molecular recorder that stores transient developmental signaling cues as permanent mutations in cellular genomes for deconstruction at later stages via single-cell transcriptomics. We applied SABER-seq to record Notch signaling in developing zebrafish brains. SABER-seq has two components: a signaling sensor and a barcode recorder. The sensor activates Cas9 in a Notch-dependent manner with inducible control while the recorder obtains mutations in ancestral cells where Notch is active. We combine SABER-seq with an expanded juvenile brain atlas to identify cell types derived from Notch-active founders. Our data reveals rare examples where differential Notch activities in ancestral progenitors are detected in terminally differentiated neuronal subtypes. SABER-seq is a novel platform for rapid, scalable and high-resolution mapping of signaling activity during development.
    Keywords:  Barcoding; Brain development; Brain scRNA-seq; CRISPR; Neurogenesis; Notch signaling
    DOI:  https://doi.org/10.1242/dev.203102
  7. bioRxiv. 2024 Oct 29. pii: 2024.10.27.620531. [Epub ahead of print]
      Measuring single-cell genomic profiles at different timepoints enables our understanding of cell development. This understanding is more comprehensive when we perform an integrative analysis of multiple measurements (or modalities) across various developmental stages. However, obtaining such measurements from the same set of single cells is resource-intensive, restricting our ability to study them integratively. We propose an unsupervised integration model, scMultiNODE, that integrates gene expression and chromatin accessibility measurements in developing single cells while preserving cell type variations and cellular dynamics. scMultiNODE uses autoencoders to learn nonlinear low-dimensional cell representation and optimal transport to align cells across different measurements. Next, it utilizes neural ordinary differential equations to explicitly model cell development with a regularization term to learn a dynamic latent space. Our experiments on four real-world developmental single-cell datasets show that scMultiNODE can integrate temporally profiled multi-modal single-cell measurements better than existing methods that focus on cell type variations and tend to ignore cellular dynamics. We also show that scMultiNODE's joint latent space helps with the downstream analysis of single-cell development.
    Availability: The data and code are publicly available at https://github.com/rsinghlab/scMultiNODE .
    DOI:  https://doi.org/10.1101/2024.10.27.620531
  8. Nature. 2024 Nov 20.
      With the convergence in exciting advances in molecular and spatial profiling methods and new computational approaches leveraging artificial intelligence and machine learning (AI/ML), the construction of cell atlases is progressing from data collection to atlas integration and beyond. Here, we explore five ways in which cell atlases, including the Human Cell Atlas, are already revealing valuable biological insights, and how they are poised to provide even greater benefits in the coming years. In particular, we discuss cell atlases as censuses of cells; as 3D maps of cells in the body, across modalities and scales; as maps connecting genotype causes to phenotype effects; as 4D maps of development; and, ultimately, as foundation models of biology unifying all these aspects and helping to transform medicine.
    DOI:  https://doi.org/10.1038/s41586-024-08338-4
  9. Nat Methods. 2024 Nov 18.
      Targeted spatial transcriptomic methods capture the topology of cell types and states in tissues at single-cell and subcellular resolution by measuring the expression of a predefined set of genes. The selection of an optimal set of probed genes is crucial for capturing the spatial signals present in a tissue. This requires selecting the most informative, yet minimal, set of genes to profile (gene set selection) for which it is possible to build probes (probe design). However, current selections often rely on marker genes, precluding them from detecting continuous spatial signals or new states. We present Spapros, an end-to-end probe set selection pipeline that optimizes both gene set specificity for cell type identification and within-cell type expression variation to resolve spatially distinct populations while considering prior knowledge as well as probe design and expression constraints. We evaluated Spapros and show that it outperforms other selection approaches in both cell type recovery and recovering expression variation beyond cell types. Furthermore, we used Spapros to design a single-cell resolution in situ hybridization on tissues (SCRINSHOT) experiment of adult lung tissue to demonstrate how probes selected with Spapros identify cell types of interest and detect spatial variation even within cell types.
    DOI:  https://doi.org/10.1038/s41592-024-02496-z
  10. Nucleic Acids Res. 2024 Nov 18. pii: gkae1100. [Epub ahead of print]
      Genomic, epigenomic and transcriptomic alterations are hallmarks of cancer cells, and are closely connected. Especially, epigenetic regulation plays a critical role in tumorigenesis and progression. The growing single-cell epigenome data in cancer research provide new opportunities for data mining from a more comprehensive perspective. However, there is still a lack of databases designed for interactively exploring the single-cell multi-omics data of human pan-cancer, especially for the single-cell epigenome data. To fill in the gap, we developed scCancerExplorer, a comprehensive and user-friendly database to facilitate the exploration of the single-cell genome, epigenome (chromatin accessibility and DNA methylation), and transcriptome data of 50 cancer types. Five major modules were provided to explore those data interactively, including 'Integrated multi-omics analysis', 'Single-cell transcriptome', 'Single-cell epigenome', 'Single-cell genome' and 'TCGA analysis'. By simple clicking, users can easily investigate gene expression features, chromatin accessibility patterns, transcription factor activities, DNA methylation states, copy number variations and TCGA survival analysis results. Taken together, scCancerExplorer is distinguished from previous databases with rich and interactive functions for exploring the single-cell multi-omics data of human pan-cancer. It bridges the gap between single-cell multi-omics data and the end-users, and will facilitate progress in the field of cancer research. scCancerExplorer is freely accessible via https://bianlab.cn/scCancerExplorer.
    DOI:  https://doi.org/10.1093/nar/gkae1100
  11. Genome Biol. 2024 Nov 21. 25(1): 297
      Understanding tumor cell heterogeneity and plasticity is crucial for overcoming drug resistance. Single-cell technologies enable analyzing cell states at a given condition, but catenating static cell snapshots to characterize dynamic drug responses remains challenging. Here, we propose scStateDynamics, an algorithm to infer tumor cell state dynamics and identify common drug effects by modeling single-cell level gene expression changes. Its reliability is validated on both simulated and lineage tracing data. Application to real tumor drug treatment datasets identifies more subtle cell subclusters with different drug responses beyond static transcriptome similarity and disentangles drug action mechanisms from the cell-level expression changes.
    Keywords:  Drug response; Dynamics; Single-cell; Tumor
    DOI:  https://doi.org/10.1186/s13059-024-03436-y
  12. bioRxiv. 2024 Nov 07. pii: 2024.11.05.622163. [Epub ahead of print]
       Background: Technological advances in sequencing and computation have allowed deep exploration of the molecular basis of diseases. Biological networks have proven to be a useful framework for interrogating omics data and modeling regulatory gene and protein interactions. Large collaborative projects, such as The Cancer Genome Atlas (TCGA), have provided a rich resource for building and validating new computational methods resulting in a plethora of open-source software for downloading, pre-processing, and analyzing those data. However, for an end-to-end analysis of regulatory networks a coherent and reusable workflow is essential to integrate all relevant packages into a robust pipeline.
    Findings: We developed tcga-data-nf, a Nextflow workflow that allows users to reproducibly infer regulatory networks from the thousands of samples in TCGA using a single command. The workflow can be divided into three main steps: multi-omics data, such as RNA-seq and methylation, are downloaded, preprocessed, and lastly used to infer regulatory network models with the netZoo software tools. The workflow is powered by the NetworkDataCompanion R package, a standalone collection of functions for managing, mapping, and filtering TCGA data. Here we show how the pipeline can be used to study the differences between colon cancer subtypes that could be explained by epigenetic mechanisms. Lastly, we provide pre-generated networks for the 10 most common cancer types that can be readily accessed.
    Conclusions: tcga-data-nf is a complete yet flexible and extensible framework that enables the reproducible inference and analysis of cancer regulatory networks, bridging a gap in the current universe of software tools.
    DOI:  https://doi.org/10.1101/2024.11.05.622163
  13. Nature. 2024 Nov;635(8039): 699-707
      The gastrointestinal tract is a multi-organ system crucial for efficient nutrient uptake and barrier immunity. Advances in genomics and a surge in gastrointestinal diseases1,2 has fuelled efforts to catalogue cells constituting gastrointestinal tissues in health and disease3. Here we present systematic integration of 25 single-cell RNA sequencing datasets spanning the entire healthy gastrointestinal tract in development and in adulthood. We uniformly processed 385 samples from 189 healthy controls using a newly developed automated quality control approach (scAutoQC), leading to a healthy reference atlas with approximately 1.1 million cells and 136 fine-grained cell states. We anchor 12 gastrointestinal disease datasets spanning gastrointestinal cancers, coeliac disease, ulcerative colitis and Crohn's disease to this reference. Utilizing this 1.6 million cell resource (gutcellatlas.org), we discover epithelial cell metaplasia originating from stem cells in intestinal inflammatory diseases with transcriptional similarity to cells found in pyloric and Brunner's glands. Although previously linked to mucosal healing4, we now implicate pyloric gland metaplastic cells in inflammation through recruitment of immune cells including T cells and neutrophils. Overall, we describe inflammation-induced changes in stem cells that alter mucosal tissue architecture and promote further inflammation, a concept applicable to other tissues and diseases.
    DOI:  https://doi.org/10.1038/s41586-024-07571-1
  14. Nature. 2024 Nov;635(8039): 523-524
      
    Keywords:  Bioinformatics; Biological techniques; Cell biology; Molecular biology; Scientific community
    DOI:  https://doi.org/10.1038/d41586-024-03754-y
  15. Nature. 2024 Nov 20.
      Uncontrolled regeneration leads to neoplastic transformation1-3. The intestinal epithelium requires precise regulation during continuous homeostatic and damage-induced tissue renewal to prevent neoplastic transformation, suggesting that pathways unlinking tumour growth from regenerative processes must exist. Here, by mining RNA-sequencing datasets from two intestinal damage models4,5 and using pharmacological, transcriptomics and genetic tools, we identified liver X receptor (LXR) pathway activation as a tissue adaptation to damage that reciprocally regulates intestinal regeneration and tumorigenesis. Using single-cell RNA sequencing, intestinal organoids, and gain- and loss-of-function experiments, we demonstrate that LXR activation in intestinal epithelial cells induces amphiregulin (Areg), enhancing regenerative responses. This response is coordinated by the LXR-ligand-producing enzyme CYP27A1, which was upregulated in damaged intestinal crypt niches. Deletion of Cyp27a1 impaired intestinal regeneration, which was rescued by exogenous LXR agonists. Notably, in tumour models, Cyp27a1 deficiency led to increased tumour growth, whereas LXR activation elicited anti-tumour responses dependent on adaptive immunity. Consistently, human colorectal cancer specimens exhibited reduced levels of CYP27A1, LXR target genes, and B and CD8 T cell gene signatures. We therefore identify an epithelial adaptation mechanism to damage, whereby LXR functions as a rheostat, promoting tissue repair while limiting tumorigenesis.
    DOI:  https://doi.org/10.1038/s41586-024-08247-6
  16. Development. 2024 Nov 15. pii: dev204212. [Epub ahead of print]151(22):
      Cell competition arises in heterogeneous tissues when neighbouring cells sense their relative fitness and undergo selection. It has been a challenge to define contexts in which cell competition is a physiologically relevant phenomenon and to understand the cellular features that underlie fitness and fitness sensing. Drawing on examples across a range of contexts and length scales, we illuminate molecular and cellular features that could underlie fitness in diverse tissue types and processes to promote and reinforce long-term maintenance of tissue function. We propose that by broadening the scope of how fitness is defined and the circumstances in which cell competition can occur, the field can unlock the potential of cell competition as a lens through which heterogeneity and its role in the fundamental principles of complex tissue organisation can be understood.
    Keywords:  Cell competition; Cell selection; Cellular fitness sensing; Complex tissue organization; Heterogeneity; Tissue robustness
    DOI:  https://doi.org/10.1242/dev.204212
  17. Nature. 2024 Nov 21.
      
    Keywords:  Cancer; Immunology; Technology
    DOI:  https://doi.org/10.1038/d41586-024-03822-3
  18. Nature. 2024 Nov;635(8039): 773-775
      
    Keywords:  Biological techniques; Computational biology and bioinformatics; Genomics; Machine learning; Technology
    DOI:  https://doi.org/10.1038/d41586-024-03762-y
  19. Nat Med. 2024 Nov 20.
      Successful pregnancy relies directly on the placenta's complex, dynamic, gene-regulatory networks. Disruption of this vast collection of intercellular and intracellular programs leads to pregnancy complications and developmental defects. In the present study, we generated a comprehensive, spatially resolved, multimodal cell census elucidating the molecular architecture of the first trimester human placenta. We utilized paired single-nucleus (sn)ATAC (assay for transposase accessible chromatin) sequencing and RNA sequencing (RNA-seq), spatial snATAC-seq and RNA-seq, and in situ sequencing and hybridization mapping of transcriptomes at molecular resolution to spatially reconstruct the joint epigenomic and transcriptomic regulatory landscape. Paired analyses unraveled intricate tumor-like gene expression and transcription factor motif programs potentially sustaining the placenta in a hostile uterine environment; further investigation of gene-linked cis-regulatory elements revealed heightened regulatory complexity that may govern trophoblast differentiation and placental disease risk. Complementary spatial mapping techniques decoded these programs within the placental villous core and extravillous trophoblast cell column architecture while simultaneously revealing niche-establishing transcriptional elements and cell-cell communication. Finally, we computationally imputed genome-wide, multiomic single-cell profiles and spatially characterized the placental chromatin accessibility landscape. This spatially resolved, single-cell multiomic framework of the first trimester human placenta serves as a blueprint for future studies on early placental development and pregnancy.
    DOI:  https://doi.org/10.1038/s41591-024-03073-9