bims-gerecp Biomed News
on Gene regulatory networks of epithelial cell plasticity
Issue of 2024‒06‒30
ten papers selected by
Xiao Qin, University of Oxford
  1. Optimal sequencing budget allocation for trajectory reconstruction of single cells.
  2. Single-cell epigenomic reconstruction of developmental trajectories from pluripotency in human neural organoid systems.
  3. Transcription factors and splice factors - interconnected regulators of stem cell differentiation.
  4. scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis.
  5. REUNION: transcription factor binding prediction and regulatory association inference from single-cell multi-omics data.
  6. Notch induces transcription by stimulating release of paused RNA Pol II without increasing chromatin accessibility.
  7. Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease.
  8. Cancer plasticity in therapy resistance: Mechanisms and novel strategies.
  9. Bridge RNAs direct programmable recombination of target and donor DNA.
  10. The New Era of Cancer Cytogenetics and Cytogenomics.
  1. Bioinformatics. 2024 Jun 28. 40(Supplement_1): i446-i452
    Optimal sequencing budget allocation for trajectory reconstruction of single cells.
    Noa Moriel, Edvin Memet, Mor Nitzan.
      BACKGROUND: Charting cellular trajectories over gene expression is key to understanding dynamic cellular processes and their underlying mechanisms. While advances in single-cell RNA-sequencing technologies and computational methods have pushed forward the recovery of such trajectories, trajectory inference remains a challenge due to the noisy, sparse, and high-dimensional nature of single-cell data. This challenge can be alleviated by increasing either the number of cells sampled along the trajectory (breadth) or the sequencing depth, i.e. the number of reads captured per cell (depth). Generally, these two factors are coupled due to an inherent breadth-depth tradeoff that arises when the sequencing budget is constrained due to financial or technical limitations.RESULTS: Here we study the optimal allocation of a fixed sequencing budget to optimize the recovery of trajectory attributes. Empirical results reveal that reconstruction accuracy of internal cell structure in expression space scales with the logarithm of either the breadth or depth of sequencing. We additionally observe a power law relationship between the optimal number of sampled cells and the corresponding sequencing budget. For linear trajectories, non-monotonicity in trajectory reconstruction across the breadth-depth tradeoff can impact downstream inference, such as expression pattern analysis along the trajectory. We demonstrate these results for five single-cell RNA-sequencing datasets encompassing differentiation of embryonic stem cells, pancreatic beta cells, hepatoblast and multipotent hematopoietic cells, as well as induced reprogramming of embryonic fibroblasts into neurons. By addressing the challenges of single-cell data, our study offers insights into maximizing the efficiency of cellular trajectory analysis through strategic allocation of sequencing resources.
    DOI:  https://doi.org/10.1093/bioinformatics/btae258
  2. Nat Neurosci. 2024 Jun 24.
    Single-cell epigenomic reconstruction of developmental trajectories from pluripotency in human neural organoid systems.
    Fides Zenk, Jonas Simon Fleck, Sophie Martina Johanna Jansen, Bijan Kashanian, Benedikt Eisinger, Małgorzata Santel, Jean-Samuel Dupré, J Gray Camp, Barbara Treutlein.
      Cell fate progression of pluripotent progenitors is strictly regulated, resulting in high human cell diversity. Epigenetic modifications also orchestrate cell fate restriction. Unveiling the epigenetic mechanisms underlying human cell diversity has been difficult. In this study, we use human brain and retina organoid models and present single-cell profiling of H3K27ac, H3K27me3 and H3K4me3 histone modifications from progenitor to differentiated neural fates to reconstruct the epigenomic trajectories regulating cell identity acquisition. We capture transitions from pluripotency through neuroepithelium to retinal and brain region and cell type specification. Switching of repressive and activating epigenetic modifications can precede and predict cell fate decisions at each stage, providing a temporal census of gene regulatory elements and transcription factors. Removing H3K27me3 at the neuroectoderm stage disrupts fate restriction, resulting in aberrant cell identity acquisition. Our single-cell epigenome-wide map of human neural organoid development serves as a blueprint to explore human cell fate determination.
    DOI:  https://doi.org/10.1038/s41593-024-01652-0
  3. Curr Stem Cell Rep. 2023 Jun;9(2): 31-41
    Transcription factors and splice factors - interconnected regulators of stem cell differentiation.
    Madison M Mehlferber, Muge Kuyumcu-Martinez, Clint L Miller, Gloria M Sheynkman.
      Purpose of review: The underlying molecular mechanisms that direct stem cell differentiation into fully functional, mature cells remain an area of ongoing investigation. Cell state is the product of the combinatorial effect of individual factors operating within a coordinated regulatory network. Here, we discuss the contribution of both gene regulatory and splicing regulatory networks in defining stem cell fate during differentiation and the critical role of protein isoforms in this process.Recent findings: We review recent experimental and computational approaches that characterize gene regulatory networks, splice regulatory networks, and the resulting transcriptome and proteome they mediate during differentiation. Such approaches include long-read RNA sequencing, which has demonstrated high-resolution profiling of mRNA isoforms, and Cas13-based CRISPR, which could make possible high-throughput isoform screening. Collectively, these developments enable systems-level profiling of factors contributing to cell state.
    Summary: Overall, gene and splice regulatory networks are important in defining cell state. The emerging high-throughput systems-level approaches will characterize the gene regulatory network components necessary in driving stem cell differentiation.
    Keywords:  Alternative Splicing; Development; Regulatory Networks; Splice Factors; Stem cells; Transcription Factors
    DOI:  https://doi.org/10.1007/s40778-023-00227-2
  4. Genome Biol. 2024 Jun 24. 25(1): 164
    scHolography: a computational method for single-cell spatial neighborhood reconstruction and analysis.
    Yuheng C Fu, Arpan Das, Dongmei Wang, Rosemary Braun, Rui Yi.
      Spatial transcriptomics has transformed our ability to study tissue complexity. However, it remains challenging to accurately dissect tissue organization at single-cell resolution. Here we introduce scHolography, a machine learning-based method designed to reconstruct single-cell spatial neighborhoods and facilitate 3D tissue visualization using spatial and single-cell RNA sequencing data. scHolography employs a high-dimensional transcriptome-to-space projection that infers spatial relationships among cells, defining spatial neighborhoods and enhancing analyses of cell-cell communication. When applied to both human and mouse datasets, scHolography enables quantitative assessments of spatial cell neighborhoods, cell-cell interactions, and tumor-immune microenvironment. Together, scHolography offers a robust computational framework for elucidating 3D tissue organization and analyzing spatial dynamics at the cellular level.
    Keywords:  Deep learning; Neural network; Single-cell spatial transcriptomics; Spatial neighborhood analysis; Stable matching neighbor
    DOI:  https://doi.org/10.1186/s13059-024-03299-3
  5. Bioinformatics. 2024 Jun 28. 40(Supplement_1): i567-i575
    REUNION: transcription factor binding prediction and regulatory association inference from single-cell multi-omics data.
    Yang Yang, Dana Pe'er.
      MOTIVATION: Profiling of gene expression and chromatin accessibility by single-cell multi-omics approaches can help to systematically decipher how transcription factors (TFs) regulate target gene expression via cis-region interactions. However, integrating information from different modalities to discover regulatory associations is challenging, in part because motif scanning approaches miss many likely TF binding sites.RESULTS: We develop REUNION, a framework for predicting genome-wide TF binding and cis-region-TF-gene "triplet" regulatory associations using single-cell multi-omics data. The first component of REUNION, Unify, utilizes information theory-inspired complementary score functions that incorporate TF expression, chromatin accessibility, and target gene expression to identify regulatory associations. The second component, Rediscover, takes Unify estimates as input for pseudo semi-supervised learning to predict TF binding in accessible genomic regions that may or may not include detected TF motifs. Rediscover leverages latent chromatin accessibility and sequence feature spaces of the genomic regions, without requiring chromatin immunoprecipitation data for model training. Applied to peripheral blood mononuclear cell data, REUNION outperforms alternative methods in TF binding prediction on average performance. In particular, it recovers missing region-TF associations from regions lacking detected motifs, which circumvents the reliance on motif scanning and facilitates discovery of novel associations involving potential co-binding transcriptional regulators. Newly identified region-TF associations, even in regions lacking a detected motif, improve the prediction of target gene expression in regulatory triplets, and are thus likely to genuinely participate in the regulation.
    AVAILABILITY AND IMPLEMENTATION: All source code is available at https://github.com/yangymargaret/REUNION.
    DOI:  https://doi.org/10.1093/bioinformatics/btae234
  6. bioRxiv. 2024 Jun 13. pii: 2024.06.13.598853. [Epub ahead of print]
    Notch induces transcription by stimulating release of paused RNA Pol II without increasing chromatin accessibility.
    Julia M Rogers, Claudia A Mimoso, Benjamin Je Martin, Alexandre P Martin, Jon C Aster, Karen Adelman, Stephen C Blacklow.
      Notch proteins undergo ligand-induced proteolysis to release a nuclear effector that influences a wide range of cellular processes by regulating transcription. Despite years of study, however, how Notch induces the transcription of its target genes remains unclear. Here, we comprehensively examined the response to human Notch1 across a time course of activation using genomic assays of nascent RNA and chromatin accessibility. These data revealed that Notch induces target gene transcription primarily by releasing paused RNA polymerase II (RNAPII), in contrast to prevailing models suggesting that Notch acts by promoting chromatin accessibility. Indeed, we found that open chromatin is established at Notch-responsive regulatory elements prior to Notch signaling, through SWI/SNF-mediated remodeling. Notch activation, however, elicited no further chromatin opening at these loci. Together, these studies reveal that the nuclear response to Notch signaling is dictated by the pre-existing chromatin state and RNAPII distribution at time of signal activation.
    DOI:  https://doi.org/10.1101/2024.06.13.598853
  7. NPJ Syst Biol Appl. 2024 Jun 24. 10(1): 69
    Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease.
    Christoph Kilian, Hanna Ulrich, Viktor A Zouboulis, Paulina Sprezyna, Jasmin Schreiber, Tomer Landsberger, Maren Büttner, Moshe Biton, Eduardo J Villablanca, Samuel Huber, Lorenz Adlung.
      Single-cell-based methods such as flow cytometry or single-cell mRNA sequencing (scRNA-seq) allow deep molecular and cellular profiling of immunological processes. Despite their high throughput, however, these measurements represent only a snapshot in time. Here, we explore how longitudinal single-cell-based datasets can be used for deterministic ordinary differential equation (ODE)-based modelling to mechanistically describe immune dynamics. We derived longitudinal changes in cell numbers of colonic cell types during inflammatory bowel disease (IBD) from flow cytometry and scRNA-seq data of murine colitis using ODE-based models. Our mathematical model generalised well across different protocols and experimental techniques, and we hypothesised that the estimated model parameters reflect biological processes. We validated this prediction of cellular turnover rates with KI-67 staining and with gene expression information from the scRNA-seq data not used for model fitting. Finally, we tested the translational relevance of the mathematical model by deconvolution of longitudinal bulk mRNA-sequencing data from a cohort of human IBD patients treated with olamkicept. We found that neutrophil depletion may contribute to IBD patients entering remission. The predictive power of IBD deterministic modelling highlights its potential to advance our understanding of immune dynamics in health and disease.
    DOI:  https://doi.org/10.1038/s41540-024-00395-9
  8. Drug Resist Updat. 2024 Jun 22. pii: S1368-7646(24)00072-4. [Epub ahead of print]76 101114
    Cancer plasticity in therapy resistance: Mechanisms and novel strategies.
    Xing Niu, Wenjing Liu, Yinling Zhang, Jing Liu, Jianjun Zhang, Bo Li, Yue Qiu, Peng Zhao, Zhongmiao Wang, Zhe Wang.
      Therapy resistance poses a significant obstacle to effective cancer treatment. Recent insights into cell plasticity as a new paradigm for understanding resistance to treatment: as cancer progresses, cancer cells experience phenotypic and molecular alterations, corporately known as cell plasticity. These alterations are caused by microenvironment factors, stochastic genetic and epigenetic changes, and/or selective pressure engendered by treatment, resulting in tumor heterogeneity and therapy resistance. Increasing evidence suggests that cancer cells display remarkable intrinsic plasticity and reversibly adapt to dynamic microenvironment conditions. Dynamic interactions between cell states and with the surrounding microenvironment form a flexible tumor ecosystem, which is able to quickly adapt to external pressure, especially treatment. Here, this review delineates the formation of cancer cell plasticity (CCP) as well as its manipulation of cancer escape from treatment. Furthermore, the intrinsic and extrinsic mechanisms driving CCP that promote the development of therapy resistance is summarized. Novel treatment strategies, e.g., inhibiting or reversing CCP is also proposed. Moreover, the review discusses the multiple lines of ongoing clinical trials globally aimed at ameliorating therapy resistance. Such advances provide directions for the development of new treatment modalities and combination therapies against CCP in the context of therapy resistance.
    Keywords:  Cancer cell plasticity; Cell fate; Combination therapy; Therapy resistance; Tumor microenvironment
    DOI:  https://doi.org/10.1016/j.drup.2024.101114
  9. Nature. 2024 Jun;630(8018): 984-993
    Bridge RNAs direct programmable recombination of target and donor DNA.
    Matthew G Durrant, Nicholas T Perry, James J Pai, Aditya R Jangid, Januka S Athukoralage, Masahiro Hiraizumi, John P McSpedon, April Pawluk, Hiroshi Nishimasu, Silvana Konermann, Patrick D Hsu.
      Genomic rearrangements, encompassing mutational changes in the genome such as insertions, deletions or inversions, are essential for genetic diversity. These rearrangements are typically orchestrated by enzymes that are involved in fundamental DNA repair processes, such as homologous recombination, or in the transposition of foreign genetic material by viruses and mobile genetic elements1,2. Here we report that IS110 insertion sequences, a family of minimal and autonomous mobile genetic elements, express a structured non-coding RNA that binds specifically to their encoded recombinase. This bridge RNA contains two internal loops encoding nucleotide stretches that base-pair with the target DNA and the donor DNA, which is the IS110 element itself. We demonstrate that the target-binding and donor-binding loops can be independently reprogrammed to direct sequence-specific recombination between two DNA molecules. This modularity enables the insertion of DNA into genomic target sites, as well as programmable DNA excision and inversion. The IS110 bridge recombination system expands the diversity of nucleic-acid-guided systems beyond CRISPR and RNA interference, offering a unified mechanism for the three fundamental DNA rearrangements-insertion, excision and inversion-that are required for genome design.
    DOI:  https://doi.org/10.1038/s41586-024-07552-4
  10. Methods Mol Biol. 2024 ;2825 3-37
    The New Era of Cancer Cytogenetics and Cytogenomics.
    Jing Christine Ye, Henry H Heng.
      The promises of the cancer genome sequencing project, combined with various -omics technologies, have raised questions about the importance of cancer cytogenetic analyses. It is suggested that DNA sequencing provides high resolution, speed, and automation, potentially replacing cytogenetic testing. We disagree with this reductionist prediction. On the contrary, various sequencing projects have unexpectedly challenged gene theory and highlighted the importance of the genome or karyotype in organizing gene network interactions. Consequently, profiling the karyotype can be more meaningful than solely profiling gene mutations, especially in cancer where karyotype alterations mediate cellular macroevolution dominance. In this chapter, recent studies that illustrate the ultimate importance of karyotype in cancer genomics and evolution are briefly reviewed. In particular, the long-ignored non-clonal chromosome aberrations or NCCAs are linked to genome or chromosome instability, genome chaos is linked to genome reorganization under cellular crisis, and the two-phased cancer evolution reconciles the relationship between genome alteration-mediated punctuated macroevolution and gene mutation-mediated stepwise microevolution. By further synthesizing, the concept of karyotype coding is discussed in the context of information management. Altogether, we call for a new era of cancer cytogenetics and cytogenomics, where an array of technical frontiers can be explored further, which is crucial for both basic research and clinical implications in the cancer field.
    Keywords:  Chromosome instability or CIN; Clonal chromosome aberrations or CCAs; Genome chaos; Karyotype coding; Non-clonal chromosome aberrations or NCCAs; Two-phased evolution; Unstable cellular supersystem
    DOI:  https://doi.org/10.1007/978-1-0716-3946-7_1
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