An official website of the United States government
One of the fundamental questions in developmental biology is how a cell is specified to differentiate as a specialized cell type. Traditionally, plant cell types were defined based on their function, location, morphology, and lineage. Currently, in the age of single-cell biology, researchers typically attempt to assign plant cells to cell types by clustering them based on their transcriptomes. However, because cells are dynamic entities that progress through the cell cycle and respond to signals, the transcriptome also reflects the state of the cell at a particular moment in time, raising questions about how to define a cell type. We suggest that these complexities and dynamics of cell states are of interest and further consider the roles signaling, stochasticity, cell cycle, and mechanical forces play in plant cell fate specification. Once established, cell identity must also be maintained. With the wealth of single-cell data coming out, the field is poised to elucidate both the complexity and dynamics of cell states.
more »
« less
This content will become publicly available on January 1, 2027
Measurement of tissue viscosity to relate force and motion in collective cell migration
Effective viscosity in epithelial cell monolayers has a wide distribution, with the width being caused by activity and the mean indicating the resistance of the cell monolayer to flow.
more »
« less
- Award ID(s):
- 2205141
- PAR ID:
- 10653768
- Publisher / Repository:
- Soft Matter
- Date Published:
- Journal Name:
- Soft Matter
- ISSN:
- 1744-683X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Binding of autoantibodies to keratinocyte surface antigens, primarily desmoglein 3 (Dsg3) of the desmosomal complex, leads to the dissociation of cell-cell adhesion in the blistering disorder pemphigus vulgaris (PV). After the initial disassembly of desmosomes, cell-cell adhesions actively remodel in association with the cytoskeleton and focal adhesions. Growing evidence highlights the role of adhesion mechanics and mechanotransduction at cell-cell adhesions in this remodeling process, as their active participation may direct autoimmune pathogenicity. However, a large part of the biophysical transformations after antibody binding remains underexplored. Specifically, it is unclear how tension in desmosomes and cell-cell adhesions changes in response to antibodies, and how the altered tensional states translate to cellular responses. Here, we showed a tension loss at Dsg3 using fluorescence resonance energy transfer (FRET)-based tension sensors, a tension loss at the entire cell-cell adhesion, and a potentially compensatory increase in junctional traction force at cell-extracellular matrix adhesions after PV antibody binding. Further, our data indicate that this tension loss is mediated by the inhibition of RhoA at cell-cell contacts, and the extent of RhoA inhibition may be crucial in determining the severity of pathogenicity among different PV antibodies. More importantly, this tension loss can be partially restored by altering actomyosin based cell contractility. Collectively, these findings provide previously unattainable details in our understanding of the mechanisms that govern cell-cell interactions under physiological and autoimmune conditions, which may open the window to entirely new therapeutics aimed at restoring physiological balance to tension dynamics that regulates the maintenance of cell-cell adhesion.more » « less
-
ABSTRACT Cells do not make fate decisions independently. Arguably, every cell-fate decision occurs in response to environmental signals. In many cases, cell-cell communication alters the dynamics of the internal gene regulatory network of a cell to initiate cell-fate transitions, yet models rarely take this into account. Here, we have developed a multiscale perspective to study the granulocyte-monocyte versus megakaryocyte-erythrocyte fate decisions. This transition is dictated by the GATA1-PU.1 network: a classical example of a bistable cell-fate system. We show that, for a wide range of cell communication topologies, even subtle changes in signaling can have pronounced effects on cell-fate decisions. We go on to show how cell-cell coupling through signaling can spontaneously break the symmetry of a homogenous cell population. Noise, both intrinsic and extrinsic, shapes the decision landscape profoundly, and affects the transcriptional dynamics underlying this important hematopoietic cell-fate decision-making system. This article has an associated ‘The people behind the papers’ interview.more » « less
-
Messenger RNAs (mRNAs) function as mobile signals for cell-to-cell communication in multicellular organisms. The KNOTTED1 (KN1) homeodomain family transcription factors act non–cell autonomously to control stem cell maintenance in plants through cell-to-cell movement of their proteins and mRNAs through plasmodesmata; however, the mechanism of mRNA movement is largely unknown. We show that cell-to-cell movement of a KN1 mRNA requires ribosomal RNA–processing protein 44A (AtRRP44A), a subunit of the RNA exosome that processes or degrades diverse RNAs in eukaryotes. AtRRP44A can interact with plasmodesmata and mediates the cell-to-cell trafficking of KN1 mRNA, and genetic analysis indicates that AtRRP44A is required for the developmental functions of SHOOT MERISTEMLESS, an Arabidopsis KN1 homolog. Our findings suggest that AtRRP44A promotes mRNA trafficking through plasmodesmata to control stem cell–dependent processes in plants.more » « less
-
Abstract In recent years, the integration of single‐cell multi‐omics data has provided a more comprehensive understanding of cell functions and internal regulatory mechanisms from a non‐single omics perspective, but it still suffers many challenges, such as omics‐variance, sparsity, cell heterogeneity, and confounding factors. As it is known, the cell cycle is regarded as a confounder when analyzing other factors in single‐cell RNA‐seq data, but it is not clear how it will work on the integrated single‐cell multi‐omics data. Here, a cell cycle‐aware network (CCAN) is developed to remove cell cycle effects from the integrated single‐cell multi‐omics data while keeping the cell type‐specific variations. This is the first computational model to study the cell‐cycle effects in the integration of single‐cell multi‐omics data. Validations on several benchmark datasets show the outstanding performance of CCAN in a variety of downstream analyses and applications, including removing cell cycle effects and batch effects of scRNA‐seq datasets from different protocols, integrating paired and unpaired scRNA‐seq and scATAC‐seq data, accurately transferring cell type labels from scRNA‐seq to scATAC‐seq data, and characterizing the differentiation process from hematopoietic stem cells to different lineages in the integration of differentiation data.more » « less
