Cell state transitions: definitions and challenges

Development ◽  
2021 ◽  
Vol 148 (20) ◽  
Author(s):  
Carla Mulas ◽  
Agathe Chaigne ◽  
Austin Smith ◽  
Kevin J. Chalut
Keyword(s):  
Biological Systems ◽  
The State ◽  
Cell Junctions ◽  
State Transitions ◽  
Cell State ◽  
Experimental Systems ◽  
Fundamental Challenge ◽  
A Cell ◽  
Different Shapes ◽  
Cell Cell

ABSTRACT A fundamental challenge when studying biological systems is the description of cell state dynamics. During transitions between cell states, a multitude of parameters may change – from the promoters that are active, to the RNAs and proteins that are expressed and modified. Cells can also adopt different shapes, alter their motility and change their reliance on cell-cell junctions or adhesion. These parameters are integral to how a cell behaves and collectively define the state a cell is in. Yet, technical challenges prevent us from measuring all of these parameters simultaneously and dynamically. How, then, can we comprehend cell state transitions using finite descriptions? The recent Company of Biologists virtual workshop entitled ‘Cell State Transitions: Approaches, Experimental Systems and Models’ attempted to address this question. Here, we summarise some of the main points that emerged during the workshop's themed discussions. We also present examples of cell state transitions and describe models and systems that are pushing forward our understanding of how cells rewire their state.

scholarly journals Vascular Endothelial-Cadherin Stabilizes at Cell–Cell Junctions by Anchoring to Circumferential Actin Bundles through α- and β-Catenins in Cyclic AMP-Epac-Rap1 Signal-activated Endothelial Cells

2010 ◽  
Vol 21 (4) ◽  
pp. 584-596 ◽  
Author(s):  
Kazuomi Noda ◽  
Jianghui Zhang ◽  
Shigetomo Fukuhara ◽  
Satoshi Kunimoto ◽  
Michihiro Yoshimura ◽  
...  
Keyword(s):  
Cell Adhesion ◽  
Classical Model ◽  
Green Fluorescence Protein ◽  
Cell Junctions ◽  
Vascular Endothelial ◽  
Cell Contacts ◽  
Actin Bundles ◽  
Dependent Cell ◽  
A Cell ◽  
Cell Cell

Vascular endothelial (VE)-cadherin is a cell–cell adhesion molecule involved in endothelial barrier functions. Previously, we reported that cAMP-Epac-Rap1 signal enhances VE-cadherin–dependent cell adhesion. Here, we further scrutinized how cAMP-Epac-Rap1 pathway promotes stabilization of VE-cadherin at the cell–cell contacts. Forskolin induced circumferential actin bundling and accumulation of VE-cadherin fused with green fluorescence protein (VEC-GFP) on the bundled actin filaments. Fluorescence recovery after photobleaching (FRAP) analyses using VEC-GFP revealed that forskolin stabilizes VE-cadherin at cell–cell contacts. These effects of forskolin were mimicked by an activator for Epac but not by that for protein kinase A. Forskolin-induced both accumulation and stabilization of junctional VEC-GFP was impeded by latrunculin A. VE-cadherin, α-catenin, and β-catenin were dispensable for forskolin-induced circumferential actin bundling, indicating that homophilic VE-cadherin association is not the trigger of actin bundling. Requirement of α- and β-catenins for forskolin-induced stabilization of VE-cadherin on the actin bundles was confirmed by FRAP analyses using VEC-GFP mutants, supporting the classical model that α-catenin could potentially link the bundled actin to cadherin. Collectively, circumferential actin bundle formation and subsequent linkage between actin bundles and VE-cadherin through α- and β-catenins are important for the stabilization of VE-cadherin at the cell–cell contacts in cAMP-Epac-Rap1 signal-activated cells.

scholarly journals CellTrans: An R Package to Quantify Stochastic Cell State Transitions

2017 ◽  
Vol 11 ◽  
pp. 117793221771224 ◽  
Author(s):  
Thomas Buder ◽  
Andreas Deutsch ◽  
Michael Seifert ◽  
Anja Voss-Böhme
Keyword(s):  
Cell Lines ◽  
Transition Probabilities ◽  
Cell Lineage ◽  
R Package ◽  
State Transitions ◽  
Cell State ◽  
Current State ◽  
Cancerous Cell ◽  
Distinct Cell ◽  
A Cell

Many normal and cancerous cell lines exhibit a stable composition of cells in distinct states which can, e.g., be defined on the basis of cell surface markers. There is evidence that such an equilibrium is associated with stochastic transitions between distinct states. Quantifying these transitions has the potential to better understand cell lineage compositions. We introduce CellTrans, an R package to quantify stochastic cell state transitions from cell state proportion data from fluorescence-activated cell sorting and flow cytometry experiments. The R package is based on a mathematical model in which cell state alterations occur due to stochastic transitions between distinct cell states whose rates only depend on the current state of a cell. CellTrans is an automated tool for estimating the underlying transition probabilities from appropriately prepared data. We point out potential analytical challenges in the quantification of these cell transitions and explain how CellTrans handles them. The applicability of CellTrans is demonstrated on publicly available data on the evolution of cell state compositions in cancer cell lines. We show that CellTrans can be used to (1) infer the transition probabilities between different cell states, (2) predict cell line compositions at a certain time, (3) predict equilibrium cell state compositions, and (4) estimate the time needed to reach this equilibrium. We provide an implementation of CellTrans in R, freely available via GitHub ( https://github.com/tbuder/CellTrans ).

scholarly journals Mapping the dynamics of force transduction at cell–cell junctions of epithelial clusters

eLife ◽  
2014 ◽  
Vol 3 ◽  
Author(s):  
Mei Rosa Ng ◽  
Achim Besser ◽  
Joan S Brugge ◽  
Gaudenz Danuser
Keyword(s):  
Cell Junctions ◽  
Force Transmission ◽  
Cell Clusters ◽  
Cell Matrix ◽  
A Cell ◽  
Experimental Approaches ◽  
Cell Adhesions ◽  
Cell Force ◽  
Cell Cell ◽  
Force Transduction

Force transduction at cell-cell adhesions regulates tissue development, maintenance and adaptation. We developed computational and experimental approaches to quantify, with both sub-cellular and multi-cellular resolution, the dynamics of force transmission in cell clusters. Applying this technology to spontaneously-forming adherent epithelial cell clusters, we found that basal force fluctuations were coupled to E-cadherin localization at the level of individual cell-cell junctions. At the multi-cellular scale, cell-cell force exchange depended on the cell position within a cluster, and was adaptive to reconfigurations due to cell divisions or positional rearrangements. Importantly, force transmission through a cell required coordinated modulation of cell-matrix adhesion and actomyosin contractility in the cell and its neighbors. These data provide insights into mechanisms that could control mechanical stress homeostasis in dynamic epithelial tissues, and highlight our methods as a resource for the study of mechanotransduction in cell-cell adhesions.

Spatially Selective Imaging of Cell‐Matrix and Cell‐Cell Junctions by Electrochemiluminescence

2021 ◽  
Author(s):  
Hao Ding ◽  
Ping Zhou ◽  
Wenxuan Fu ◽  
Lurong Ding ◽  
Weiliang Guo ◽  
...  
Keyword(s):  
Cell Junctions ◽  
Cell Matrix ◽  
Cell Cell

Cross-species integration of single-cell RNA-seq resolved alveolar-epithelial transitional states in idiopathic pulmonary fibrosis

2021 ◽  
Author(s):  
Kevin Y. Huang ◽  
Enrico Petretto
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Single Cell ◽  
Transitional Cell ◽  
Notch Pathway ◽  
Alveolar Epithelium ◽  
State Transitions ◽  
Specific Cell ◽  
Differentiation Process ◽  
Cell State

Single-cell transcriptomics analyses of the fibrotic lung uncovered two cell states critical to lung injury recovery in the alveolar epithelium- a reparative transitional cell state in the mouse and a disease-specific cell state (KRT5-/KRT17+) in human idiopathic pulmonary fibrosis (IPF). The murine transitional cell state lies between the differentiation from type 2 (AT2) to type 1 pneumocyte (AT1), and the human KRT5-/KRT17+ cell state may arise from the dysregulation of this differentiation process. We review major findings of single-cell transcriptomics analyses of the fibrotic lung and re-analyzed data from 7 single-cell RNA sequencing studies of human and murine models of IPF, focusing on the alveolar epithelium. Our comparative and cross-species single-cell transcriptomics analyses allowed us to further delineate the differentiation trajectories from AT2 to AT1 and AT2 to the KRT5-/KRT17+ cell state. We observed AT1 cells in human IPF retain the transcriptional signature of the murine transitional cell state. Using pseudotime analysis, we recapitulated the differentiation trajectories from AT2 to AT1 and from AT2 to KRT5-/KRT17+ cell state in multiple human IPF studies. We further delineated transcriptional programs underlying cell state transitions and determined the molecular phenotypes at terminal differentiation. We hypothesize that in addition to the reactivation of developmental programs (SOX4, SOX9), senescence (TP63, SOX4) and the Notch pathway (HES1) are predicted to steer intermediate progenitors to the KRT5-/KRT17+ cell state. Our analyses suggest that activation of SMAD3 later in the differentiation process may explain the fibrotic molecular phenotype typical of KRT5-/KRT17+ cells.

scholarly journals Enhanced Piezoelectric Fibered Extracellular Matrix to Promote Cardiomyocyte Maturation and Tissue Formation: A 3D Computational Model

Biology ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 135
Author(s):  
Pau Urdeitx ◽  
Mohamed H. Doweidar
Keyword(s):  
Extracellular Matrix ◽  
Cell Migration ◽  
Computational Models ◽  
Cell Junctions ◽  
Tissue Formation ◽  
Cardiac Muscle Cells ◽  
Cell Processes ◽  
Electrical Stimuli ◽  
Cell Cell

Mechanical and electrical stimuli play a key role in tissue formation, guiding cell processes such as cell migration, differentiation, maturation, and apoptosis. Monitoring and controlling these stimuli on in vitro experiments is not straightforward due to the coupling of these different stimuli. In addition, active and reciprocal cell–cell and cell–extracellular matrix interactions are essential to be considered during formation of complex tissue such as myocardial tissue. In this sense, computational models can offer new perspectives and key information on the cell microenvironment. Thus, we present a new computational 3D model, based on the Finite Element Method, where a complex extracellular matrix with piezoelectric properties interacts with cardiac muscle cells during the first steps of tissue formation. This model includes collective behavior and cell processes such as cell migration, maturation, differentiation, proliferation, and apoptosis. The model has employed to study the initial stages of in vitro cardiac aggregate formation, considering cell–cell junctions, under different extracellular matrix configurations. Three different cases have been purposed to evaluate cell behavior in fibered, mechanically stimulated fibered, and mechanically stimulated piezoelectric fibered extra-cellular matrix. In this last case, the cells are guided by the coupling of mechanical and electrical stimuli. Accordingly, the obtained results show the formation of more elongated groups and enhancement in cell proliferation.

scholarly journals Integrated multiscale biomaterials experiment and modelling: a perspective

2016 ◽  
Vol 6 (1) ◽  
pp. 20150098 ◽  
Author(s):  
Markus J. Buehler ◽  
Guy M. Genin
Keyword(s):  
State Of The Art ◽  
Biological Systems ◽  
The State ◽  
Computational Power ◽  
Multiscale Models ◽  
Predictive Capacity ◽  
Hierarchical Levels ◽  
Challenges And Opportunities

Advances in multiscale models and computational power have enabled a broad toolset to predict how molecules, cells, tissues and organs behave and develop. A key theme in biological systems is the emergence of macroscale behaviour from collective behaviours across a range of length and timescales, and a key element of these models is therefore hierarchical simulation. However, this predictive capacity has far outstripped our ability to validate predictions experimentally, particularly when multiple hierarchical levels are involved. The state of the art represents careful integration of multiscale experiment and modelling, and yields not only validation, but also insights into deformation and relaxation mechanisms across scales. We present here a sampling of key results that highlight both challenges and opportunities for integrated multiscale experiment and modelling in biological systems.

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