bims-gerecp 2025-02-09 papers

bims-gerecp

Biomed News

on Gene regulatory networks of epithelial cell plasticity

Issue of 2025–02–09
eight papers selected by
Xiao Qin, University of Oxford

Defining the regulatory logic of breast cancer using single-cell epigenetic and transcriptome profiling.
Oncofetal reprogramming induces phenotypic heterogeneity in colorectal cancer.
Deterministic genetic barcoding for multiplexed behavioral and single-cell transcriptomic studies.
Inferring cell trajectories of spatial transcriptomics via optimal transport analysis.
Dynamic Reprogramming of Stromal Pdgfra-expressing cells during WNT-Mediated Transformation of the Intestinal Epithelium.
How are researchers using AI? Survey reveals pros and cons for science.
Bridging the gap between science and survival.
Spatial integration of multi-omics single-cell data with SIMO.

Cell Genom. 2025 Jan 28. pii: S2666-979X(25)00021-7. [Epub ahead of print] 100765

Defining the regulatory logic of breast cancer using single-cell epigenetic and transcriptome profiling.

Matthew J Regner, Susana Garcia-Recio, Aatish Thennavan, Kamila Wisniewska, Raul Mendez-Giraldez, Brooke Felsheim, Philip M Spanheimer, Joel S Parker, Charles M Perou, Hector L Franco.

  Annotation of cis-regulatory elements that drive transcriptional dysregulation in cancer cells is critical to understanding tumor biology. Herein, we present matched chromatin accessibility (single-cell assay for transposase-accessible chromatin by sequencing [scATAC-seq]) and transcriptome (single-cell RNA sequencing [scRNA-seq]) profiles at single-cell resolution from human breast tumors and healthy mammary tissues processed immediately following surgical resection. We identify the most likely cell of origin for subtype-specific breast tumors and implement linear mixed-effects modeling to quantify associations between regulatory elements and gene expression in malignant versus normal cells. These data unveil cancer-specific regulatory elements and putative silencer-to-enhancer switching events in cells that lead to the upregulation of clinically relevant oncogenes. In addition, we generate matched scATAC-seq and scRNA-seq profiles for breast cancer cell lines, revealing a conserved oncogenic gene expression program between in vitro and in vivo cells. This work highlights the importance of non-coding regulatory mechanisms that underlie oncogenic processes and the ability of single-cell multi-omics to define the regulatory logic of cancer cells.

Keywords:  breast cancer; chromatin accessibility; enhancer elements; gene regulation; scATAC-seq; scRNA-seq; single-cell genomics; single-cell multi-omics

DOI:  https://doi.org/10.1016/j.xgen.2025.100765
Nat Genet. 2025 Feb 07.

Oncofetal reprogramming induces phenotypic heterogeneity in colorectal cancer.

DOI: https://doi.org/10.1038/s41588-025-02092-7
Elife. 2025 Feb 05. pii: RP88334. [Epub ahead of print]12

Deterministic genetic barcoding for multiplexed behavioral and single-cell transcriptomic studies.

Jorge Blanco Mendana, Margaret Donovan, Lindsey Gengelbach O'Brien, Benjamin Auch, John Garbe, Daryl M Gohl.

  Advances in single-cell sequencing technologies have provided novel insights into the dynamics of gene expression and cellular heterogeneity within tissues and have enabled the construction of transcriptomic cell atlases. However, linking anatomical information to transcriptomic data and positively identifying the cell types that correspond to gene expression clusters in single-cell sequencing data sets remains a challenge. We describe a straightforward genetic barcoding approach that takes advantage of the powerful genetic tools in Drosophila to allow in vivo tagging of defined cell populations. This method, called Targeted Genetically-Encoded Multiplexing (TaG-EM), involves inserting a DNA barcode just upstream of the polyadenylation site in a Gal4-inducible UAS-GFP construct so that the barcode sequence can be read out during single-cell sequencing, labeling a cell population of interest. By creating many such independently barcoded fly strains, TaG-EM enables positive identification of cell types in cell atlas projects, identification of multiplet droplets, and barcoding of experimental timepoints, conditions, and replicates. Furthermore, we demonstrate that TaG-EM barcodes can be read out using next-generation sequencing to facilitate population-scale behavioral measurements. Thus, TaG-EM has the potential to enable large-scale behavioral screens in addition to improving the ability to multiplex and reliably annotate single-cell transcriptomic experiments.

Keywords:  D. melanogaster; behavior; genetic barcoding; genetics; genomics; next-generation sequencing; single-cell transcriptomics

DOI:  https://doi.org/10.7554/eLife.88334
Cell Syst. 2025 Jan 27. pii: S2405-4712(25)00027-4. [Epub ahead of print] 101194

Inferring cell trajectories of spatial transcriptomics via optimal transport analysis.

Xunan Shen, Lulu Zuo, Zhongfei Ye, Zhongyang Yuan, Ke Huang, Zeyu Li, Qichao Yu, Xuanxuan Zou, Xiaoyu Wei, Ping Xu, Yaqi Deng, Xin Jin, Xun Xu, Liang Wu, Hongmei Zhu, Pengfei Qin.

  The integration of cell transcriptomics and spatial position to organize differentiation trajectories remains a challenge. Here, we introduce SpaTrack, which leverages optimal transport to reconcile both gene expression and spatial position from spatial transcriptomics into the transition costs, thereby reconstructing cell differentiation. SpaTrack can construct detailed spatial trajectories that reflect the differentiation topology and trace cell dynamics across multiple samples over temporal intervals. To capture the dynamic drivers of differentiation, SpaTrack models cell fate as a function of expression profiles influenced by transcription factors over time. By applying SpaTrack, we successfully disentangle spatiotemporal trajectories of axolotl telencephalon regeneration and mouse midbrain development. Diverse malignant lineages expanding within a primary tumor are uncovered. One lineage, characterized by upregulated epithelial mesenchymal transition, implants at the metastatic site and subsequently colonizes to form a secondary tumor. Overall, SpaTrack efficiently advances trajectory inference from spatial transcriptomics, providing valuable insights into differentiation processes.

Keywords:  cell differentiation; optimal transport; spatial transcriptomics; trajectory inference

DOI:  https://doi.org/10.1016/j.cels.2025.101194
bioRxiv. 2025 Jan 25. pii: 2025.01.22.634326. [Epub ahead of print]

Dynamic Reprogramming of Stromal Pdgfra-expressing cells during WNT-Mediated Transformation of the Intestinal Epithelium.

O Pellon-Cardenas, P Rout, S Hassan, E Fokas, He Ping, I Patel, J Patel, O Plotsker, A Wu, R Kumar, M Akther, A Logerfo, S Wu, D E Wagner, D Boffelli, K D Walton, E Manieri, K Tong, J R Spence, N J Bessman, R A Shivdasani, M P Verzi.

Stromal fibroblasts regulate critical signaling gradients along the intestinal crypt-villus axis 1 and provide a niche that supports adjacent epithelial stem cells. Here we report that Pdgfra -expressing fibroblasts secrete ligands that promote a regenerative-like state in the intestinal mucosa during early WNT-mediated tumorigenesis. Using a mouse model of WNT-driven oncogenesis and single-cell RNA sequencing (RNA-seq) of mesenchyme cell populations, we revealed a dynamic reprogramming of Pdgfra + fibroblasts that facilitates WNT-mediated tissue transformation. Functional assays of potential mediators of cell-to-cell communication between these fibroblasts and the oncogenic epithelium revealed that TGFB signaling is notably induced in Pdgfra + fibroblasts in the presence of oncogenic epithelium, and TGFB was essential to sustain regenerative-like growth of organoids ex vivo . Genetic reduction of Cdx2 in the β-catenin mutant epithelium elevated the fetal-like/regenerative transcriptome and accelerated WNT-dependent onset of oncogenic transformation of the tissue in vivo . These results demonstrate that Pdgfra + fibroblasts are activated during WNT-driven oncogenesis to promote a regenerative state in the epithelium that precedes and facilitates formation of tumors.

DOI: https://doi.org/10.1101/2025.01.22.634326
Nature. 2025 Feb 04.

How are researchers using AI? Survey reveals pros and cons for science.

Miryam Naddaf.



Keywords:  Machine learning; Publishing; Scientific community

DOI:  https://doi.org/10.1038/d41586-025-00343-5
Nat Rev Gastroenterol Hepatol. 2025 Feb 07.

Bridging the gap between science and survival.

Ahsen Ustaoglu.

DOI: https://doi.org/10.1038/s41575-025-01044-0
Nat Commun. 2025 Feb 01. 16(1): 1265

Spatial integration of multi-omics single-cell data with SIMO.

Penghui Yang, Kaiyu Jin, Yue Yao, Lijun Jin, Xin Shao, Chengyu Li, Xiaoyan Lu, Xiaohui Fan.

Technical limitations in spatial and single-cell omics sequencing pose challenges for capturing and describing multimodal information at the spatial scale. To address this, we develop SIMO, a computational method designed for the Spatial Integration of Multi-Omics datasets through probabilistic alignment. Unlike previous tools, SIMO not only integrates spatial transcriptomics with single-cell RNA-seq but expands beyond, enabling integration across multiple single-cell modalities, such as chromatin accessibility and DNA methylation, which have not been co-profiled spatially before. We benchmark SIMO on simulated datasets, demonstrating its high accuracy and robustness. Further application on biological datasets reveals SIMO's ability to detect topological patterns of cells and their regulatory modes across multiple omics layers. Through comprehensive analysis of real-world data, SIMO uncovers multimodal spatial heterogeneity, offering deeper insights into the spatial organization and regulation of biological molecules. These findings position SIMO as a powerful tool for advancing spatial biology by revealing previously inaccessible multimodal insights.

DOI: https://doi.org/10.1038/s41467-025-56523-4