Science AdvancesGenomicsPeer-reviewed journal article
Genomic signatures of the unjamming transition in compressed human bronchial epithelial cells
Margherita De MarzioiD, Ayşe KılıçiD, Enrico MaiorinoiD, Jennifer A. MitcheliD, Chimwemwe MwaseiD, Michael J. O’SullivaniD, Maureen McGill, Robert ChaseiD, Jeffrey J. FredbergiD, Jin‐Ah ParkiD, Kimberly GlassiD, Scott T. WeissiD
Abstract
Epithelial tissue has the capacity to switch from a collective phase that is quiescent, solidlike and non-migratory to one that is dynamic, fluid-like and migratory. In certain physiological and pathophysiological contexts this phenotypic switch has been attributed not to the well-known epithelial-to-mesenchymal transition, EMT, but rather to the recently discovered unjamming transition, UJT. UJT has been characterized thus far mainly at functional and morphological levels whereas underlying genome-wide molecular events remain largely unexplored. Using primary human bronchial epithelial cells and one well-defined trigger of UJT -mechanical compression- here we combine temporal RNA-Seq data and Protein-Protein Interaction networks to provide the first genome-wide analysis of UJT. Our results show that compression induces a multiphasic transcriptional response characterized by an early activation of genes regulating the membrane and actomyosin structure, and a delayed activation of genes regulating the extracellular matrix and cellmatrix interactions. This biphasic response is mediated by a cascade of signaling processes that promotes actin polymerization through the recruitment of integrin-ECM adhesive complexes and promotes increased cellular motility through activation of AP-1 transcription factors via ERK and JNK pathways. These findings, taken together, show that the UJT program is not the result of any single signaling pathway but rather comprises a coordinated interplay of downstream pathways including development, fate selection, energy metabolism, cytoskeletal reorganization, and adhesive interaction with extracellular matrix.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- research focus: trajectory inference
- approach: statistical model
- Citations
- 38
- FWCI
- 3.27
- Field percentile
- top 7%
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