Molecular mechanism for direct actin force-sensing by α-catenin
Abstract
The actin cytoskeleton mediates mechanical coupling between cells and their tissue microenvironments. The architecture and composition of actin networks are modulated by force, but it is unclear how interactions between actin filaments (F-actin) and associated proteins are mechanically regulated. Here, we employ both optical trapping and biochemical reconstitution with myosin motor proteins to show single piconewton forces applied solely to F-actin enhance binding by the human version of the essential cell-cell adhesion protein αE-catenin, but not its homolog vinculin. Cryo-electron microscopy structures of both proteins bound to F-actin reveal unique rearrangements that facilitate their flexible C-termini refolding to engage distinct interfaces. Truncating α-catenin's C-terminus eliminates force-activated F-actin binding, and addition of this motif to vinculin confers force-activated binding, demonstrating that α-catenin's C-terminus is a modular detector of F-actin tension. Our studies establish that piconewton force on F-actin can enhance partner binding, which we propose mechanically regulates cellular adhesion through a-catenin.
Data availability
The atomic coordinates for the metavinculin ABD-F-actin complex and α-catenin ABD-F-actin complex have been deposited in the Protein Data Bank (PDB) with accession codes 6UPW and 6UPV, and the corresponding cryo-EM density maps in the Electron Microscopy Data Bank (EMDB) with accession codes EMD-20844 and EMD-20843.The code for analyzing TIRF movies is freely available as an ImageJ plugin with a graphical user interface at https://github.com/alushinlab/ActinEnrichment. All other data are available in the manuscript or supplementary materials.
Article and author information
Author details
Funding
Irma T. Hirschl Trust (Research Award)
- Gregory M Alushin
Pew Charitable Trusts (Pew Scholar Award)
- Gregory M Alushin
National Institutes of Health (5DP5OD017885)
- Gregory M Alushin
National Institutes of Health (1DP2HG010510)
- Shixin Liu
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2020, Mei et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 6,031
- views
-
- 906
- downloads
-
- 74
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Cell Biology
- Neuroscience
The claustrum complex is viewed as fundamental for higher-order cognition; however, the circuit organization and function of its neuroanatomical subregions are not well understood. We demonstrated that some of the key roles of the CLA complex can be attributed to the connectivity and function of a small group of neurons in its ventral subregion, the endopiriform (EN). We identified a subpopulation of EN neurons by their projection to the ventral CA1 (ENvCA1-proj. neurons), embedded in recurrent circuits with other EN neurons and the piriform cortex. Although the ENvCA1-proj. neuron activity was biased toward novelty across stimulus categories, their chemogenetic inhibition selectively disrupted the memory-guided but not innate responses of mice to novelty. Based on our functional connectivity analysis, we suggest that ENvCA1-proj. neurons serve as an essential node for recognition memory through recurrent circuits mediating sustained attention to novelty, and through feed-forward inhibition of distal vCA1 neurons shifting memory-guided behavior from familiarity to novelty.
-
- Cell Biology
- Computational and Systems Biology
Induced pluripotent stem cell (iPSC) technology is revolutionizing cell biology. However, the variability between individual iPSC lines and the lack of efficient technology to comprehensively characterize iPSC-derived cell types hinder its adoption in routine preclinical screening settings. To facilitate the validation of iPSC-derived cell culture composition, we have implemented an imaging assay based on cell painting and convolutional neural networks to recognize cell types in dense and mixed cultures with high fidelity. We have benchmarked our approach using pure and mixed cultures of neuroblastoma and astrocytoma cell lines and attained a classification accuracy above 96%. Through iterative data erosion, we found that inputs containing the nuclear region of interest and its close environment, allow achieving equally high classification accuracy as inputs containing the whole cell for semi-confluent cultures and preserved prediction accuracy even in very dense cultures. We then applied this regionally restricted cell profiling approach to evaluate the differentiation status of iPSC-derived neural cultures, by determining the ratio of postmitotic neurons and neural progenitors. We found that the cell-based prediction significantly outperformed an approach in which the population-level time in culture was used as a classification criterion (96% vs 86%, respectively). In mixed iPSC-derived neuronal cultures, microglia could be unequivocally discriminated from neurons, regardless of their reactivity state, and a tiered strategy allowed for further distinguishing activated from non-activated cell states, albeit with lower accuracy. Thus, morphological single-cell profiling provides a means to quantify cell composition in complex mixed neural cultures and holds promise for use in the quality control of iPSC-derived cell culture models.