More Like this

1. Cell-mediated matrix deformations and cell–cell adhesions determine epithelial collective cell migration phenotypes

   https://doi.org/10.1063/5.0295506  

   Leonard, Corinne E; Lichtenberg, Jessanne Y; Sterling, Hazel R; Rolston, Jesse; Tran, Sydnie K; Hwang, Priscilla Y (December 2025, APL Bioengineering)

   Successful development of tissue structures requires different collective cell migration patterns or phenotypes. Two examples of collective migration phenotypes in epithelial morphogenic processes, such as tubulogenesis, are rotational and invasive. Rotational collective migration phenotypes (RCM) typically lead to acinar structures, and invasive collective migration (ICM) phenotypes lead to duct-like structures. How cells adopt these different phenotypes is still largely unknown. Here, we investigate how cell–cell adhesion marker P-cadherin (CDH3) and mechanical cell–matrix interactions, including matrix deformations, protrusions, and focal adhesions, control rotational or invasive phenotypes during tubulogenesis. To accomplish our objective, we created a custom 3D microfluidic assay to perform live-cell imaging of epithelial clusters or cysts [wild-type (WT) and CDH3-depleted (CDH3-/-)] undergoing tubulogenesis, while simultaneously measuring matrix deformation rates. Our findings reveal WT epithelial cysts maintain rotational phenotypes, but transition to an invasive phenotype to undergo tubulogenesis. Furthermore, we demonstrate ICM phenotypes correlate with higher matrix deformation rates compared to rotational phenotypes. Our studies reveal CDH3 is required for epithelial cysts to transition from rotational to ICM phenotypes, associated with decreased matrix deformation rates. Without CDH3, epithelial cysts lose their ability to adopt ICM phenotypes, which can be rescued by RhoA activation. Finally, we demonstrate that the RhoA-rescued ICM phenotype is mediated, in part, by increased matrix deformation rates and vinculin recruitment to focal adhesion sites. 

   more » « less
2. Build-a-Cell: Engineering a Synthetic Cell Community

   https://doi.org/10.3390/life11111176  

   Frischmon, Caroline; Sorenson, Carlise; Winikoff, Michael; Adamala, Katarzyna P (November 2021, Life)

   Build-a-Cell is a global network of researchers that aims to develop synthetic living cells within the next decade. These cells will revolutionize the biotechnology industry by providing scientists and engineers with a more complete understanding of biology. Researchers can already replicate many cellular functions individually, but combining them into a single cell remains a significant challenge. This integration step will require the type of large-scale collaboration made possible by Build-a-Cell’s open, collective structure. Beyond the lab, Build-a-Cell addresses policy issues and biosecurity concerns associated with synthetic cells. The following review discusses Build-a-Cell’s history, function, and goals. 

   more » « less
3. Dissecting crosstalk induced by cell-cell communication using single-cell transcriptomic data

   https://doi.org/10.1038/s41467-025-61149-7  

   Hou, Jiawen; Zhao, Wei; Nie, Qing (December 2025, Nature Communications)

   Abstract During cell-cell communication (CCC), pathways activated by different ligand-receptor pairs may have crosstalk with each other. While multiple methods have been developed to infer CCC networks and their downstream response using single-cell RNA-seq data (scRNA-seq), the potential crosstalk between pathways connecting CCC with its downstream targets has been ignored. Here we introduce a machine learning-based method SigXTalk to analyze the crosstalk using scRNA-seq data by quantifying signal fidelity and specificity, two critical quantities measuring the effect of crosstalk. Specifically, a hypergraph learning method is used to encode the higher-order relations among receptors, transcription factors and target genes within regulatory pathways. Benchmarking of SigXTalk using simulation and real-world data shows the effectiveness, robustness, and accuracy in identifying key shared molecules among crosstalk pathways and their roles in transferring shared CCC information. Analysis of disease data shows SigXTalk’s capability in identifying crucial signals, targets, regulatory networks, and CCC patterns that distinguish different disease conditions. Applications to the data with multiple time points reveals SigXTalk’s capability in tracking the evolution of crosstalk pathways over time. Together our studies provide a systematic analysis of CCC-induced regulatory networks from the perspective of crosstalk between pathways. 

   more » « less
4. Multiscale Cell–Cell Interactive Spatial Transcriptomics Analysis

   https://doi.org/10.1002/advs.202508358  

   Cottrell, Sean; Wei, Guo‐Wei (November 2025, Advanced Science)

   Abstract Spatial transcriptomics data analysis integrates gene expression profiles with their corresponding spatial locations to identify spatial domains, infer cell‐type dynamics, and detect gene expression patterns within tissues. However, the current spatial transcriptomics analysis neglects the multiscale cell–cell interactions that are crucial in biology. To fill this gap, multiscale cell–cell interactive spatial transcriptomics (MCIST) analysis is proposed. MCIST combines the advantages of an ensemble of multiscale topological representations of cell–cell interactions in the gene expression space with those of cutting edge spatial deep learning techniques. MCIST is validated by a comparison of 14 cutting‐edge methods on a huge collection of 37 benchmark spatial transcriptomics datasets. It is demonstrated that MCIST yields superior performance in spatial domain detection. It achieves the best clustering score on 23/37 datasets and is among the top three methods on 33/37 datasets, while the second best method scored only 6/37 and 17/37 on these measures, respectively. In terms of overall performance with respect to a quantitative metric, MCIST offers more than an 11% improvement to the previous state‐of‐the‐art in spatial domain detection. In addition, MCIST offers multiscale insights with respect to trajectory inference, differentially expressed gene detection, and signaling pathway enrichment analysis. This MCIST sheds valuable light on the multiscale perspective in spatial transcriptomics. 

   more » « less
5. Subcellular positioning during cell division and cell plate formation in maize

   https://doi.org/10.3389/fpls.2023.1204889  

   Allsman, Lindy A.; Bellinger, Marschal A.; Huang, Vivian; Duong, Matthew; Contreras, Alondra; Romero, Andrea N.; Verboonen, Benjamin; Sidhu, Sukhmani; Zhang, Xiaoguo; Steinkraus, Holly; et al (July 2023, Frontiers in Plant Science)

   IntroductionDuring proliferative plant cell division, the new cell wall, called the cell plate, is first built in the middle of the cell and then expands outward to complete cytokinesis. This dynamic process requires coordinated movement and arrangement of the cytoskeleton and organelles. MethodsHere we use live-cell markers to track the dynamic reorganization of microtubules, nuclei, endoplasmic reticulum, and endomembrane compartments during division and the formation of the cell plate in maize leaf epidermal cells. ResultsThe microtubule plus-end localized protein END BINDING1 (EB1) highlighted increasing microtubule dynamicity during mitosis to support rapid changes in microtubule structures. The localization of the cell-plate specific syntaxin KNOLLE, several RAB-GTPases, as well as two plasma membrane localized proteins was assessed after treatment with the cytokinesis-specific callose-deposition inhibitor Endosidin7 (ES7) and the microtubule-disrupting herbicide chlorpropham (CIPC). While ES7 caused cell plate defects inArabidopsis thaliana, it did not alter callose accumulation, or disrupt cell plate formation in maize. In contrast, CIPC treatment of maize epidermal cells occasionally produced irregular cell plates that split or fragmented, but did not otherwise disrupt the accumulation of cell-plate localized proteins. DiscussionTogether, these markers provide a robust suite of tools to examine subcellular trafficking and organellar organization during mitosis and cell plate formation in maize. 

   more » « less