Hemidesmosomes are specialized cell-matrix adhesion structures that are associated with the keratin cytoskeleton. Although the adhesion function of hemidesmosomes has been extensively studied, their role in mechanosignaling and transduction remains largely unexplored. Here, we show that keratinocytes lacking hemidesmosomal integrin α6β4 exhibit increased focal adhesion formation, cell spreading, and traction-force generation. Moreover, disruption of the interaction between α6β4 and intermediate filaments or laminin-332 results in similar phenotypical changes. We further demonstrate that integrin α6β4 regulates the activity of the mechanosensitive transcriptional regulator YAP through inhibition of Rho–ROCK–MLC– and FAK–PI3K–dependent signaling pathways. Additionally, increased tension caused by impaired hemidesmosome assembly leads to a redistribution of integrin αVβ5 from clathrin lattices to focal adhesions. Our results reveal a novel role for hemidesmosomes as regulators of cellular mechanical forces and establish the existence of a mechanical coupling between adhesion complexes.

Ion channels regulate cell proliferation, differentiation, and migration in normal and neoplastic cells through cell-cell and cell-extracellular matrix (ECM) transmembrane receptors called integrins. K + flux through the human ether-à-gogo-related gene 1 (hERG1) channel shapes action potential firing in excitable cells such as cardiomyocytes. Its abundance is often aberrantly high in tumors, where it modulates integrin-mediated signaling. We found that hERG1 interacted with the b 1 integrin subunit at the plasma membrane of human cancer cells. This interaction was not detected in cardiomyocytes because of the presence of the hERG1 auxiliary subunit KCNE1 (potassium voltage-gated channel subfamily E regulatory subunit 1), which blocked the b 1 integrin-hERG1 interaction. Although open hERG1 channels did not interact as strongly with b 1 integrins as did closed channels, current flow through hERG1 channels was necessary to activate the integrin-dependent phosphorylation of Tyr 397 in focal adhesion kinase (FAK) in both normal and cancer cells. In immunodeficient mice, proliferation was inhibited in breast cancer cells expressing forms of hERG1 with impaired K + flow, whereas metastasis of breast cancer cells was reduced when the hERG1/b 1 integrin interaction was disrupted. We conclude that the interaction of b 1 integrins with hERG1 channels in cancer cells stimulated distinct signaling pathways that depended on the conformational state of hERG1 and affected different aspects of tumor progression.

Transcriptional rates are often estimated by fitting the distribution of mature mRNA numbers measured using smFISH (single molecule fluorescence in situ hybridization) with the distribution predicted by the telegraph model of gene expression, which defines two promoter states of activity and inactivity. However, fluctuations in mature mRNA numbers are strongly affected by processes downstream of transcription. In addition, the telegraph model assumes one gene copy, but in experiments cells may have two gene copies as cells replicate their genome during the cell cycle. Whilst it is often presumed that post-transcriptional noise and gene copy number variation affect transcriptional parameter estimation, the size of the error introduced remains unclear. To address this issue, here we measure both mature and nascent mRNA distributions of GAL10 in yeast cells using smFISH and classify each cell according to its cell cycle phase. We infer transcriptional parameters from mature and nascent mRNA distributions, with and without accounting for cell cycle phase and compare the results to live-cell transcription measurements of the same gene. We find that: (i) correcting for cell cycle dynamics decreases the promoter switching rates and the initiation rate, and increases the fraction of time spent in the active state, as well as the burst size; (ii) additional correction for post-transcriptional noise leads to further increases in the burst size and to a large reduction in the errors in parameter estimation. Furthermore, we outline how to correctly adjust for measurement noise in smFISH due to uncertainty in transcription site localisation when introns cannot be labelled. Simulations with parameters estimated from nascent smFISH data, which is corrected for cell cycle phases and measurement noise, leads to autocorrelation functions that agree with those obtained from live-cell imaging.