Please read Dr. Ghaddar’s article in Nucleic Acids Research titled, “Reconstructing physical cell interaction networks from single-cell data using Neighbor-seq.“
The spatial context of cells in a tissue and their resulting cell–cell communications influence numerous processes, including cellular differentiation, organ development and homeostasis, and immune interactions in disease. Few high-throughput methods exist that can resolve direct cellular communications in vivo at single-cell resolution. Single-cell RNA sequencing (scRNA-seq) can identify cell-types and states in heterogeneous tissues, but the tissue structure is largely destroyed in the process. Microscopy-based methods such as RNAscope and FISH can interrogate only preselected genes at high spatial resolution. Spatial transcriptomics allows profiling of microscopic regions, but still samples 10–100 cells per region. Sequencing of partially dissociated tissues and subsequent multiplet deconvolution permits inference of physical cell interactions, but this requires specialized experimental modifications. A general method that can infer direct cell–cell interactions and concurrent transcriptomic changes in vivo at single cell resolution would provide unprecedented insight into the building blocks of tissue architecture in healthy and diseased tissues. To read the full article.
Reconstructing physical cell interaction networks from single-cell data using Neighbor-seq. Ghaddar B, De S. Nucleic Acids Res. 2022 May 10:gkac333. PMID: 35536255 DOI: 1093/nar/gkac333