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1. Cell alignment modulated by surface nano-topography – Roles of cell-matrix and cell-cell interactions

   https://doi.org/10.1016/j.actbio.2022.01.057  

   Coyle, Stephen; Doss, Bryant; Huo, Yucheng; Singh, Hemang Raj; Quinn, David; Jimmy Hsia, K.; LeDuc, Philip R. (April 2022, Acta Biomaterialia)
2. Inference and analysis of cell-cell communication using CellChat

   https://doi.org/10.1038/s41467-021-21246-9  

   Jin, Suoqin; Guerrero-Juarez, Christian_F; Zhang, Lihua; Chang, Ivan; Ramos, Raul; Kuan, Chen-Hsiang; Myung, Peggy; Plikus, Maksim_V; Nie, Qing (February 2021, Nature Communications)

   Abstract Understanding global communications among cells requires accurate representation of cell-cell signaling links and effective systems-level analyses of those links. We construct a database of interactions among ligands, receptors and their cofactors that accurately represent known heteromeric molecular complexes. We then develop CellChat, a tool that is able to quantitatively infer and analyze intercellular communication networks from single-cell RNA-sequencing (scRNA-seq) data. CellChat predicts major signaling inputs and outputs for cells and how those cells and signals coordinate for functions using network analysis and pattern recognition approaches. Through manifold learning and quantitative contrasts, CellChat classifies signaling pathways and delineates conserved and context-specific pathways across different datasets. Applying CellChat to mouse and human skin datasets shows its ability to extract complex signaling patterns. Our versatile and easy-to-use toolkit CellChat and a web-based Explorer (http://www.cellchat.org/) will help discover novel intercellular communications and build cell-cell communication atlases in diverse tissues. 

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3. Molecular basis of sidekick-mediated cell-cell adhesion and specificity

   https://doi.org/10.7554/eLife.19058  

   Goodman, Kerry M; Yamagata, Masahito; Jin, Xiangshu; Mannepalli, Seetha; Katsamba, Phinikoula S; Ahlsén, Göran; Sergeeva, Alina P; Honig, Barry; Sanes, Joshua R; Shapiro, Lawrence (September 2016, eLife)

   Sidekick (Sdk) 1 and 2 are related immunoglobulin superfamily cell adhesion proteins required for appropriate synaptic connections between specific subtypes of retinal neurons. Sdks mediate cell-cell adhesion with homophilic specificity that underlies their neuronal targeting function. Here we report crystal structures of Sdk1 and Sdk2 ectodomain regions, revealing similar homodimers mediated by the four N-terminal immunoglobulin domains (Ig1–4), arranged in a horseshoe conformation. These Ig1–4 horseshoes interact in a novel back-to-back orientation in both homodimers through Ig1:Ig2, Ig1:Ig1 and Ig3:Ig4 interactions. Structure-guided mutagenesis results show that this canonical dimer is required for both Sdk-mediated cell aggregation (via trans interactions) and Sdk clustering in isolated cells (via cis interactions). Sdk1/Sdk2 recognition specificity is encoded across Ig1–4, with Ig1–2 conferring the majority of binding affinity and differential specificity. We suggest that competition between cis and trans interactions provides a novel mechanism to sharpen the specificity of cell-cell interactions. 

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4. Single-Cell RNA-Seq Analysis Reveals the Acquisition of Cancer Stem Cell Traits and Increase of Cell–Cell Signaling during EMT Progression

   https://doi.org/10.3390/cancers13225726  

   Bocci, Federico; Zhou, Peijie; Nie, Qing (November 2021, Cancers)

   Intermediate cell states (ICSs) during the epithelial–mesenchymal transition (EMT) are emerging as a driving force of cancer invasion and metastasis. ICSs typically exhibit hybrid epithelial/mesenchymal characteristics as well as cancer stem cell (CSC) traits including proliferation and drug resistance. Here, we analyze several single-cell RNA-seq (scRNA-seq) datasets to investigate the relation between several axes of cancer progression including EMT, CSC traits, and cell–cell signaling. To accomplish this task, we integrate computational methods for clustering and trajectory inference with analysis of EMT gene signatures, CSC markers, and cell–cell signaling pathways, and highlight conserved and specific processes across the datasets. Our analysis reveals that “standard” measures of pluripotency often used in developmental contexts do not necessarily correlate with EMT progression and expression of CSC-related markers. Conversely, an EMT circuit energy that quantifies the co-expression of epithelial and mesenchymal genes consistently increases along EMT trajectories across different cancer types and anatomical locations. Moreover, despite the high context specificity of signal transduction across different cell types, cells undergoing EMT always increased their potential to send and receive signals from other cells. 

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5. Adhesion Protein Structure, Molecular Affinities, and Principles of Cell-Cell Recognition

   https://doi.org/10.1016/j.cell.2020.04.010  

   Honig, Barry; Shapiro, Lawrence (April 2020, Cell)